Triple
T13118197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivien Merchant |
E311150
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Daniel Pinter
Daniel Pinter is the son of Nobel Prize–winning British playwright Harold Pinter and actress Vivien Merchant.
|
E1041836
|
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: Daniel Pinter | Statement: [Vivien Merchant, child, Daniel Pinter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Pinter Context triple: [Vivien Merchant, child, Daniel Pinter]
-
A.
Marc Zamarin
Marc Zamarin is a sports executive best known for serving as the general manager of the Philadelphia Wings professional lacrosse team.
-
B.
Marc Mezvinsky
Marc Mezvinsky is an American investment banker best known as the husband of Chelsea Clinton and son-in-law of former U.S. President Bill Clinton and former Secretary of State Hillary Clinton.
-
C.
Jeremy Kushnier
Jeremy Kushnier is a Canadian actor and singer best known for his work in musical theatre, including roles in productions like "Rent" and "Footloose."
-
D.
Daniel Zelman
Daniel Zelman is an American actor, screenwriter, and television producer known for co-creating the legal thriller series "Damages."
-
E.
Daniel Rappaport
Daniel Rappaport is a film producer known for working on mainstream Hollywood comedies, including the movie "Office Christmas Party."
- 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: Daniel Pinter Triple: [Vivien Merchant, child, Daniel Pinter]
Generated description
Daniel Pinter is the son of Nobel Prize–winning British playwright Harold Pinter and actress Vivien Merchant.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daniel Pinter Target entity description: Daniel Pinter is the son of Nobel Prize–winning British playwright Harold Pinter and actress Vivien Merchant.
-
A.
Marc Zamarin
Marc Zamarin is a sports executive best known for serving as the general manager of the Philadelphia Wings professional lacrosse team.
-
B.
Marc Mezvinsky
Marc Mezvinsky is an American investment banker best known as the husband of Chelsea Clinton and son-in-law of former U.S. President Bill Clinton and former Secretary of State Hillary Clinton.
-
C.
Jeremy Kushnier
Jeremy Kushnier is a Canadian actor and singer best known for his work in musical theatre, including roles in productions like "Rent" and "Footloose."
-
D.
Daniel Zelman
Daniel Zelman is an American actor, screenwriter, and television producer known for co-creating the legal thriller series "Damages."
-
E.
Daniel Rappaport
Daniel Rappaport is a film producer known for working on mainstream Hollywood comedies, including the movie "Office Christmas Party."
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98182011c8190a504678affbb7787 |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7460c05bc819089cdd004bb07c492 |
completed | May 3, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_69f749ffd5d4819096cee1b27838d7d3 |
completed | May 3, 2026, 1:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f74a58aa948190978568028cc5a445 |
completed | May 3, 2026, 1:15 p.m. |
Created at: April 9, 2026, 9:06 p.m.