Triple
T21780780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonjour Tristesse (film) |
E537704
|
entity |
| Predicate | blackAndWhiteSequences |
P68467
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bonjour Tristesse (film), blackAndWhiteSequences, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: blackAndWhiteSequences Context triple: [Bonjour Tristesse (film), blackAndWhiteSequences, yes]
-
A.
blackAndWhite
Indicates that something is presented or exists in only black and white, without any other colors.
-
B.
workBlackAndWhite
chosen
Indicates that the work is presented in black and white rather than in color.
-
C.
isBlackAndWhiteEpisodeOf
Indicates that an episode is a black-and-white version belonging to a particular series or show.
-
D.
numberOfMatchesForAllBlacks
Indicates the total count of matches or occurrences involving all black entities in the given context.
-
E.
letterSequence
Indicates that one sequence of letters directly follows or is ordered in relation to another within a larger string or alphabetic arrangement.
- 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0462cae6481908d3e7f71683d8921 |
completed | April 28, 2026, 5:31 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:52 p.m.