Triple
T6009887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Common Lisp |
E133804
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
Dylan
Dylan is a multi-paradigm programming language designed for dynamic, object-oriented application development, known for combining Lisp-like semantics with a more conventional, infix syntax.
|
E561566
|
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: Dylan | Statement: [Common Lisp, influenced, Dylan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dylan Context triple: [Common Lisp, influenced, Dylan]
-
A.
Dylan
Dylan is one of the children of Tanzanian Bongo Flava star and music entrepreneur Diamond Platnumz.
-
B.
Dylan
Dylan is a masculine given name of Welsh origin, widely used in English-speaking countries.
-
C.
Dylan
Dylan is a surname most famously associated with American singer-songwriter Bob Dylan and his artistic family.
-
D.
Sir Dylan
Sir Dylan is a music producer best known for his work on Miguel’s album "War & Leisure."
-
E.
Cas and Dylan
Cas and Dylan is a 2013 Canadian road trip dramedy film starring Tatiana Maslany and Richard Dreyfuss, following an unlikely friendship that develops during a cross-country journey.
- 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: Dylan Triple: [Common Lisp, influenced, Dylan]
Generated description
Dylan is a multi-paradigm programming language designed for dynamic, object-oriented application development, known for combining Lisp-like semantics with a more conventional, infix syntax.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dylan Target entity description: Dylan is a multi-paradigm programming language designed for dynamic, object-oriented application development, known for combining Lisp-like semantics with a more conventional, infix syntax.
-
A.
Dylan
Dylan is one of the children of Tanzanian Bongo Flava star and music entrepreneur Diamond Platnumz.
-
B.
Dylan
Dylan is a masculine given name of Welsh origin, widely used in English-speaking countries.
-
C.
Dylan
Dylan is a surname most famously associated with American singer-songwriter Bob Dylan and his artistic family.
-
D.
Sir Dylan
Sir Dylan is a music producer best known for his work on Miguel’s album "War & Leisure."
-
E.
Cas and Dylan
Cas and Dylan is a 2013 Canadian road trip dramedy film starring Tatiana Maslany and Richard Dreyfuss, following an unlikely friendship that develops during a cross-country journey.
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f4e27a881909cc3f7fef62abc3b |
completed | March 22, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1089bd870819096c0f6c7cf484c50 |
completed | March 23, 2026, 9:32 a.m. |
| NEDg | Description generation | batch_69c10b0c23d48190a9e683858c29449d |
completed | March 23, 2026, 9:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c10bb3dd6481909d61d2cda5150ea7 |
completed | March 23, 2026, 9:45 a.m. |
Created at: March 22, 2026, 4:06 p.m.