Triple
T6388854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen Clark |
E143767
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Peter Davis
Peter Davis is a New Zealand academic and sociologist best known as the husband of former Prime Minister Helen Clark.
|
E598523
|
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: Peter Davis | Statement: [Helen Clark, spouse, Peter Davis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Davis Context triple: [Helen Clark, spouse, Peter Davis]
-
A.
Peter S. Davis
Peter S. Davis is a film producer best known for his work on genre films, including the Highlander franchise.
-
B.
Andrew Z. Davis
Andrew Z. Davis is a film producer best known for his work on the crime thriller "Training Day."
-
C.
Michael Dorman
Michael Dorman is an Australian actor known for his roles in television series such as "For All Mankind," "Patriot," and "The Secret Life of Us."
-
D.
Peter Howard
Peter Howard was a prominent American musical theatre orchestrator and dance music arranger known for his work on numerous Broadway productions.
-
E.
Bob Davies
Bob Davies was an American Hall of Fame point guard renowned for leading the Rochester Royals to early professional basketball success in the 1940s and 1950s.
- 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: Peter Davis Triple: [Helen Clark, spouse, Peter Davis]
Generated description
Peter Davis is a New Zealand academic and sociologist best known as the husband of former Prime Minister Helen Clark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Davis Target entity description: Peter Davis is a New Zealand academic and sociologist best known as the husband of former Prime Minister Helen Clark.
-
A.
Peter S. Davis
Peter S. Davis is a film producer best known for his work on genre films, including the Highlander franchise.
-
B.
Andrew Z. Davis
Andrew Z. Davis is a film producer best known for his work on the crime thriller "Training Day."
-
C.
Michael Dorman
Michael Dorman is an Australian actor known for his roles in television series such as "For All Mankind," "Patriot," and "The Secret Life of Us."
-
D.
Peter Howard
Peter Howard was a prominent American musical theatre orchestrator and dance music arranger known for his work on numerous Broadway productions.
-
E.
Bob Davies
Bob Davies was an American Hall of Fame point guard renowned for leading the Rochester Royals to early professional basketball success in the 1940s and 1950s.
- 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_69c008dac1ec81909cef8157ccd69962 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0686b4f34819088ff07185b34e536 |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c67c3f115481909879d637fc231556 |
completed | March 27, 2026, 12:46 p.m. |
| NEDg | Description generation | batch_69c67cfd2a4481908296d1000741b702 |
completed | March 27, 2026, 12:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c67d488f70819091a7927d06da47c3 |
completed | March 27, 2026, 12:51 p.m. |
Created at: March 22, 2026, 4:34 p.m.