Triple
T3121845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooke |
E65201
|
entity |
| Predicate | isRelatedSurname |
P3889
|
FINISHED |
| Object | Cook |
E10881
|
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: Cook | Statement: [Cooke, isRelatedSurname, Cook]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cook Context triple: [Cooke, isRelatedSurname, Cook]
-
A.
Cook
chosen
Cook is a surname shared by various notable individuals, including members of singer-songwriter Alicia Keys' family.
-
B.
Cook
Cook is a character in Geoffrey Chaucer’s "The Canterbury Tales," depicted as a London tradesman known for his culinary skills and unsanitary kitchen practices.
-
C.
Cuoco
Cuoco is an Italian surname most prominently associated with American actress Kaley Cuoco, known for her role in the television series "The Big Bang Theory."
-
D.
Chef
Chef is a 2014 American comedy-drama film written, directed by, and starring Jon Favreau as a chef who reinvents his career and life by starting a food truck business.
-
E.
Swedish Chef
The Swedish Chef is a comedic Muppet character known for his mock-Swedish gibberish, chaotic cooking antics, and slapstick humor.
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada52ab05c819088204bbb608c837c |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224cf54088190a069b4eef0a5f7d2 |
completed | March 12, 2026, 2:28 a.m. |
Created at: March 8, 2026, 3:04 p.m.