Triple
T987372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zellig Harris |
E21308
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object |
University of Pennsylvania Department of Linguistics
The University of Pennsylvania Department of Linguistics is a leading academic center for theoretical and empirical linguistics research and education, known for its influential contributions to syntax, phonology, sociolinguistics, and computational linguistics.
|
E116653
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: University of Pennsylvania Department of Linguistics | Statement: [Zellig Harris, memberOf, University of Pennsylvania Department of Linguistics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: University of Pennsylvania Department of Linguistics Context triple: [Zellig Harris, memberOf, University of Pennsylvania Department of Linguistics]
-
A.
Hungarian Research Centre for Linguistics
The Hungarian Research Centre for Linguistics is a leading Hungarian academic institution dedicated to the scientific study, documentation, and standardization of the Hungarian language and related linguistic fields.
-
B.
Language Technologies Institute, Carnegie Mellon University
The Language Technologies Institute at Carnegie Mellon University is a leading research and education center focused on areas such as natural language processing, machine learning for language, speech recognition, and related AI-driven language technologies.
-
C.
Department of English
The Department of English at Presidency College, Kolkata is an academic unit specializing in the study and teaching of English language and literature.
-
D.
Society for Linguistic Anthropology
The Society for Linguistic Anthropology is a scholarly organization dedicated to the study of language as a cultural and social resource and practice within the broader field of anthropology.
-
E.
Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge
The Faculty of Modern and Medieval Languages and Linguistics at the University of Cambridge is a leading academic division specializing in the study and research of European and global languages, their literatures, cultures, and linguistic structures.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: University of Pennsylvania Department of Linguistics Triple: [Zellig Harris, memberOf, University of Pennsylvania Department of Linguistics]
Generated description
The University of Pennsylvania Department of Linguistics is a leading academic center for theoretical and empirical linguistics research and education, known for its influential contributions to syntax, phonology, sociolinguistics, and computational linguistics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: University of Pennsylvania Department of Linguistics Target entity description: The University of Pennsylvania Department of Linguistics is a leading academic center for theoretical and empirical linguistics research and education, known for its influential contributions to syntax, phonology, sociolinguistics, and computational linguistics.
-
A.
Hungarian Research Centre for Linguistics
The Hungarian Research Centre for Linguistics is a leading Hungarian academic institution dedicated to the scientific study, documentation, and standardization of the Hungarian language and related linguistic fields.
-
B.
Language Technologies Institute, Carnegie Mellon University
The Language Technologies Institute at Carnegie Mellon University is a leading research and education center focused on areas such as natural language processing, machine learning for language, speech recognition, and related AI-driven language technologies.
-
C.
Department of English
The Department of English at Presidency College, Kolkata is an academic unit specializing in the study and teaching of English language and literature.
-
D.
Society for Linguistic Anthropology
The Society for Linguistic Anthropology is a scholarly organization dedicated to the study of language as a cultural and social resource and practice within the broader field of anthropology.
-
E.
Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge
The Faculty of Modern and Medieval Languages and Linguistics at the University of Cambridge is a leading academic division specializing in the study and research of European and global languages, their literatures, cultures, and linguistic structures.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4a7754c8190a10ba0587bd8323d |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1ce5c0d48190ab023cec30b2c25a |
completed | March 7, 2026, 12:41 p.m. |
| NEDg | Description generation | batch_69ac20a7f47c8190b765cde3c6fbe1f8 |
completed | March 7, 2026, 12:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac21640a8c8190820a1b34a7d5c895 |
completed | March 7, 2026, 1 p.m. |
Created at: March 1, 2026, 7:41 p.m.