Triple
T2351463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawkeye (TV series) |
E47456
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Kate Bishop |
E257930
|
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: Kate Bishop | Statement: [Hawkeye (TV series), character, Kate Bishop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Bishop Context triple: [Hawkeye (TV series), character, Kate Bishop]
-
A.
Kate Bishop
chosen
Kate Bishop is a young, skilled archer and protégé of Clint Barton in the Marvel universe who takes up the Hawkeye mantle.
-
B.
Alex Scott
Alex Scott was an Australian actor known for his work in film and television, including a role in the controversial 1992 drama "Romper Stomper."
-
C.
Amanda Reed
Amanda Reed was the benefactor whose bequest and vision led to the establishment of Reed College in Portland, Oregon.
-
D.
Selina Kyle
Selina Kyle is a cunning and morally ambiguous cat burglar in the Batman universe, best known by her alter ego Catwoman.
-
E.
Miss Quill
Miss Quill is a sharp-tongued, battle-hardened alien freedom fighter and teacher from the Doctor Who spin-off series "Class."
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3c37c448190b2d1fd5c404e0050 |
completed | March 9, 2026, 11:49 a.m. |
Created at: March 4, 2026, 7:54 p.m.