Triple
T17886708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Grant |
E447217
|
entity |
| Predicate | mentorOf |
P7251
|
FINISHED |
| Object | Catwoman |
—
|
NE NERFINISHED |
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: Catwoman | Statement: [Ted Grant, mentorOf, Catwoman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Catwoman Context triple: [Ted Grant, mentorOf, Catwoman]
-
A.
Selina Kyle
chosen
Selina Kyle is a cunning and morally ambiguous cat burglar in the Batman universe, best known by her alter ego Catwoman.
-
B.
Barbara Minerva
Barbara Minerva is a DC Comics character best known as the archaeologist who becomes the supervillain Cheetah and one of Wonder Woman’s primary adversaries.
-
C.
Kate Kane
Kate Kane is the DC Comics superheroine who becomes Batwoman, a vigilante crime-fighter in Gotham City and cousin to Bruce Wayne.
-
D.
Catwoman (score)
Catwoman (score) is the musical soundtrack composed by Klaus Badelt for the 2004 superhero film "Catwoman."
-
E.
Harley Quinn
Harley Quinn is a chaotic, acrobatic antiheroine from DC Comics known for her clown-themed appearance, unpredictable behavior, and complex relationship with the Joker.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c13bd288190a0302010ba4d0532 |
completed | April 19, 2026, 9:10 a.m. |
Created at: April 10, 2026, 10:18 a.m.