Triple
T13253911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Gabriel |
E315606
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jill Moore |
E315606
|
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: Jill Moore | Statement: [Peter Gabriel, spouse, Jill Moore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jill Moore Context triple: [Peter Gabriel, spouse, Jill Moore]
-
A.
Jill Moore
chosen
Jill Moore is best known as the former wife of English musician and former Genesis frontman Peter Gabriel.
-
B.
Jill Munroe
Jill Munroe is a fictional private investigator and one of the original "Angels" from the television series Charlie's Angels, portrayed by Farrah Fawcett.
-
C.
Tina Moore
Tina Moore is best known as the wife of legendary England football captain Bobby Moore and for her public life alongside him during his playing career.
-
D.
Jill Talley
Jill Talley is an American actress and voice actress best known for her work on animated television series such as SpongeBob SquarePants and various Adult Swim and comedy projects.
-
E.
Jill Richardson
Jill Richardson is the central protagonist of the film "Crossroads," around whom the story’s main events and character relationships revolve.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f7517048190b4eac4e44e81ff66 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0d3cf3881908fdfc56bd31e5fe2 |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 9:24 p.m.