Triple
T23100433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wonder Woman |
E576008
|
entity |
| Predicate | alterEgo |
P39
|
FINISHED |
| Object | Diana Prince |
—
|
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: Diana Prince | Statement: [Wonder Woman, alterEgo, Diana Prince]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diana Prince Context triple: [Wonder Woman, alterEgo, Diana Prince]
-
A.
Diana Prince
chosen
Diana Prince is the Amazonian warrior princess better known as Wonder Woman, a DC Comics superhero who leaves her hidden island to protect humanity.
-
B.
Melissa Dyne
Melissa Dyne is an American artist and musician best known as a member of the experimental pop duo The Blow, where she contributes to the group’s sound design and conceptual production.
-
C.
Jo Grant
Jo Grant is a spirited and resourceful companion of the Third Doctor in the classic British science fiction series Doctor Who.
-
D.
Jennifer Walters
Jennifer Walters is a Marvel Comics lawyer who becomes the superhero She-Hulk after receiving a blood transfusion from her cousin Bruce Banner.
-
E.
Kate Kane
Kate Kane is the DC Comics superheroine who becomes Batwoman, a vigilante crime-fighter in Gotham City and cousin to Bruce Wayne.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de8c5b4819095cddf989cade60d |
completed | April 29, 2026, 4:49 a.m. |
Created at: April 17, 2026, 3:58 p.m.