Triple
T36231833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sally (TV series) |
E891264
|
entity |
| Predicate | airedInBlackAndWhite |
P184789
|
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: [Sally (TV series), airedInBlackAndWhite, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airedInBlackAndWhite Context triple: [Sally (TV series), airedInBlackAndWhite, true]
-
A.
blackAndWhite
Indicates that something is presented or exists in only black and white, without any other colors.
-
B.
playedInBlackAndWhiteOrColorFilm
Indicates that the subject participated in a film, regardless of whether it was produced in black-and-white or in color.
-
C.
workBlackAndWhite
Indicates that the work is presented in black and white rather than in color.
-
D.
airedIn
Indicates that a media work was broadcast or shown during a specific time period or in a particular airing context.
-
E.
blackAndWhiteFilmCharacter
Indicates that a character appears in, is associated with, or belongs to a black-and-white film.
- F. None of above. chosen
Provenance (4 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_69f76e4387048190a1b27bcbf4ec7423 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b5f89c5c8190825ed5d4317c540c |
completed | May 3, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b57aa0848190a22c31c3ff90e0ab |
completed | May 3, 2026, 8:52 p.m. |
Created at: May 3, 2026, 4:09 p.m.