Triple
T15987694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke and Laura wedding |
E387738
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Bobbie Spencer |
E393999
|
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: Bobbie Spencer | Statement: [Luke and Laura wedding, hasCharacter, Bobbie Spencer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bobbie Spencer Context triple: [Luke and Laura wedding, hasCharacter, Bobbie Spencer]
-
A.
Bobbie Spencer
chosen
Bobbie Spencer is a long-running, central character on the American soap opera "General Hospital," known for her complex personal history and work as a nurse in Port Charles.
-
B.
Bobbie Wickham
Bobbie Wickham is a lively, impulsive young woman in P. G. Wodehouse’s Jeeves and Wooster stories, known for her mischievous schemes and romantic entanglements with Bertie Wooster.
-
C.
Bobbie Duncan
Bobbie Duncan is a musician best known as a member of the pioneering proto-punk band Death.
-
D.
Bobbie Carle
Bobbie Carle is best known as the wife of celebrated children's book author and illustrator Eric Carle.
-
E.
Deanna Bowers
Deanna Bowers, better known by her stage name Dee Wallace, is an American actress recognized for her roles in films such as "E.T. the Extra-Terrestrial" and numerous horror movies.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1575993948190a05d60fc9d0c05fa |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f7f439c8190b4bcd84e35aa291e |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 4:54 a.m.