Triple
T3043180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Cook |
E83179
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Stephen Cook |
E83179
|
NE FINISHED |
How this triple was built (2 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: Stephen Cook | Statement: [Stephen Cook, name, Stephen Cook]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Cook Context triple: [Stephen Cook, name, Stephen Cook]
-
A.
Stephen Cook
chosen
Stephen Cook is a Canadian-American computer scientist renowned for founding the field of computational complexity theory, particularly through his seminal work on NP-completeness.
-
B.
Leslie Valiant
Leslie Valiant is a renowned computer scientist known for his foundational work in computational learning theory, complexity theory, and artificial intelligence.
-
C.
Thomas Forster
Thomas Forster is a Jacobite military leader best known for commanding the rebel forces during the 1715 Jacobite rising in England.
-
D.
Martin Davis
Martin Davis was an American mathematician and logician renowned for his foundational work in computability theory and the Entscheidungsproblem, including contributions to the Davis–Putnam algorithm.
-
E.
Ken Sallows
Ken Sallows is an Australian film editor known for his work on numerous feature films and television productions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b5d2a308190b4ce20efcae9b761 |
completed | March 8, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1ded35e008190be7dd72aa7537a3b |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3:01 p.m.