Triple
T8395737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wonder Woman 1984 |
E198047
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Diana Prince |
E199708
|
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: Diana Prince | Statement: [Wonder Woman 1984, character, Diana Prince]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diana Prince Context triple: [Wonder Woman 1984, character, 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.
Jo Grant
Jo Grant is a spirited and resourceful companion of the Third Doctor in the classic British science fiction series Doctor Who.
-
C.
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.
-
D.
Kate Kane
Kate Kane is the DC Comics superheroine who becomes Batwoman, a vigilante crime-fighter in Gotham City and cousin to Bruce Wayne.
-
E.
Elastigirl
Elastigirl is a flexible, shape-shifting superhero and mother from Pixar's "The Incredibles" known for her elastic powers and leadership within the Parr family.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb81874d6c8190bbc0ac832d8a339d |
completed | March 31, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde85ee7b08190bfbcbed0edb142dd |
completed | April 2, 2026, 3:54 a.m. |
Created at: March 30, 2026, 6:04 p.m.