Triple
T11521860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerry Travers |
E273181
|
entity |
| Predicate | blackAndWhiteAppearance |
P3490
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Jerry Travers, blackAndWhiteAppearance, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: blackAndWhiteAppearance Context triple: [Jerry Travers, blackAndWhiteAppearance, true]
-
A.
blackAndWhite
chosen
Indicates that something is presented or exists in only black and white, without any other colors.
-
B.
workBlackAndWhite
Indicates that the work is presented in black and white rather than in color.
-
C.
blackAndWhiteFilmCharacter
Indicates that a character appears in, is associated with, or belongs to a black-and-white film.
-
D.
blackAndWhiteCategoryIntroduced
Indicates that a black-and-white category was first established, defined, or brought into use in a given context or system.
-
E.
isBlackAndWhiteEpisodeOf
Indicates that an episode is a black-and-white version belonging to a particular series or show.
- F. None of above.
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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fd129c88190893b95222480e04a |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:37 p.m.