Triple
T12859844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Therese Belivet |
E307554
|
entity |
| Predicate | loveInterest |
P7325
|
FINISHED |
| Object | Carol Aird |
E1123900
|
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: Carol Aird | Statement: [Therese Belivet, loveInterest, Carol Aird]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carol Aird Context triple: [Therese Belivet, loveInterest, Carol Aird]
-
A.
Carol Aird
chosen
Carol Aird is the elegant, enigmatic older woman at the center of Patricia Highsmith’s novel and the film "Carol," whose forbidden romance with a younger woman drives the story’s emotional core.
-
B.
Kathleen Gawthrop
Kathleen Gawthrop is best known as the second wife of legendary American golfer Arnold Palmer.
-
C.
Carol Orchard
Carol Orchard is an English nurse best known as the second wife of poet Ted Hughes, whom she married in 1970.
-
D.
Carol Vanstone
Carol Vanstone is a high-powered, no-nonsense CEO and the sister of a laid-back branch manager in the comedy film "Office Christmas Party."
-
E.
Doreen Brett
Doreen Brett was the wife of British comedian and actor Norman Wisdom.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970242bd48190941cbae0315ebc3d |
completed | April 10, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b366470819093a74828e2a85116 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 9, 2026, 5:37 p.m.