Triple
T8395705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birds of Prey |
E198046
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Black Canary |
E447237
|
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: Black Canary | Statement: [Birds of Prey, character, Black Canary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Black Canary Context triple: [Birds of Prey, character, Black Canary]
-
A.
Black Canary
chosen
Black Canary is a DC Comics superheroine known for her expert martial arts skills and her powerful ultrasonic "canary cry" sonic scream.
-
B.
Kate Kane
Kate Kane is the DC Comics superheroine who becomes Batwoman, a vigilante crime-fighter in Gotham City and cousin to Bruce Wayne.
-
C.
Hawkgirl (DCAU)
Hawkgirl (DCAU) is the animated incarnation of the DC Comics superhero and Thanagarian warrior Shayera Hol, a mace-wielding member of the Justice League known for her fierce combat skills and complex loyalties.
-
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.
Elasti-Woman
Elasti-Woman is a DC Comics superheroine and member of the Doom Patrol who can dramatically alter the size and shape of her body.
- 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.