Triple
T15484893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. F. C. Harrison |
E377019
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Cleveland
Cleveland is a common English given name and surname, historically used in Britain and the United States.
|
E18149
|
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: Cleveland | Statement: [J. F. C. Harrison, givenName, Cleveland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cleveland Context triple: [J. F. C. Harrison, givenName, Cleveland]
-
A.
Cleveland
Cleveland is a small city in northeastern Georgia known as a gateway to the Appalachian Mountains and nearby gold-mining and outdoor recreation areas.
-
B.
Cleveland
Cleveland is a historic industrial and coastal area in North East England, traditionally associated with ironstone mining and steelmaking.
-
C.
Cleveland
Cleveland is a major city in the U.S. state of Ohio, known for its industrial history, cultural institutions like the Rock and Roll Hall of Fame, and its location on the southern shore of Lake Erie.
-
D.
Cleveland
Cleveland is a fictional character who serves as the central protagonist in the story "The Pirate."
-
E.
Cleveland
Cleveland is a small city in Cass County, Missouri, United States.
- 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: Cleveland Triple: [J. F. C. Harrison, givenName, Cleveland]
Generated description
Cleveland is a common English given name and surname, historically used in Britain and the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cleveland Target entity description: Cleveland is a common English given name and surname, historically used in Britain and the United States.
-
A.
Cleveland
chosen
Cleveland is a common English surname most prominently associated with Grover Cleveland, the 22nd and 24th president of the United States.
-
B.
Cleveland
Cleveland is a historic industrial and coastal area in North East England, traditionally associated with ironstone mining and steelmaking.
-
C.
Cleveland
Cleveland is a major city in the U.S. state of Ohio, known for its industrial history, cultural institutions like the Rock and Roll Hall of Fame, and its location on the southern shore of Lake Erie.
-
D.
Cleveland
Cleveland is a small city in northeastern Georgia known as a gateway to the Appalachian Mountains and nearby gold-mining and outdoor recreation areas.
-
E.
Cleveland
Cleveland is a coastal suburb and transport hub in Redland City, Queensland, Australia, serving as a key gateway to the nearby Moreton Bay Islands.
- F. None of above.
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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8e6ff08190b130b3a38f4190e7 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ec4e868819092739e71118d43b0 |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff72a0d92c81909a3ae6e5ef81bbe8 |
completed | May 9, 2026, 5:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff730ca26c8190b6b2999926600e88 |
completed | May 9, 2026, 5:46 p.m. |
Created at: April 10, 2026, 3:46 a.m.