Triple
T15493285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spider-Man Noir |
E378749
|
entity |
| Predicate | enemy |
P4567
|
FINISHED |
| Object | Vulture (Noir) |
E344143
|
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: Vulture (Noir) | Statement: [Spider-Man Noir, enemy, Vulture (Noir)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vulture (Noir) Context triple: [Spider-Man Noir, enemy, Vulture (Noir)]
-
A.
The Vulture
The Vulture is a 1970 novel by Gil Scott-Heron that blends crime fiction with sharp social commentary on race, poverty, and urban life in Harlem.
-
B.
Vulture
chosen
Vulture is a Marvel Comics supervillain, best known as one of Spider-Man’s earliest and recurring adversaries who uses a specialized winged suit to fly and commit crimes.
-
C.
Vulture
Vulture is an online entertainment and culture website known for its in-depth coverage of television, movies, music, and pop culture.
-
D.
Fatale
Fatale is a comic book series blending noir crime and supernatural horror, created by writer Ed Brubaker and artist Sean Phillips.
-
E.
Terret Noir
Terret Noir is a light-colored, relatively rare French wine grape variety traditionally used in southern Rhône and Languedoc blends for its freshness and acidity.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fad723481908d2aa33e8f065f2f |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d48f17c819088c4d8c2d2b368c8 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 3:49 a.m.