Triple
T20253372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faraway, So Close! |
E498616
|
entity |
| Predicate | hasBlackAndWhiteSequences |
P89846
|
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: [Faraway, So Close!, hasBlackAndWhiteSequences, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBlackAndWhiteSequences Context triple: [Faraway, So Close!, hasBlackAndWhiteSequences, true]
-
A.
hasBlackAndWhiteEpisodes
Indicates that the subject includes or features episodes presented in black and white.
-
B.
hasAnimatedSequences
chosen
Indicates that the subject contains or includes one or more animated sequences.
-
C.
isBlackAndWhiteEpisodeOf
Indicates that an episode is a black-and-white version belonging to a particular series or show.
-
D.
blackAndWhite
Indicates that something is presented or exists in only black and white, without any other colors.
-
E.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a986e08190b1ff2992ed5f8772 |
completed | April 20, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e55b1b23f88190bdcbe2f81dd226dd |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:41 p.m.