Triple
T863407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love in the Time of Cholera |
E18646
|
entity |
| Predicate | filmAdaptationReleaseYear |
P2376
|
FINISHED |
| Object | 2007 |
—
|
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: 2007 | Statement: [Love in the Time of Cholera, filmAdaptationReleaseYear, 2007]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmAdaptationReleaseYear Context triple: [Love in the Time of Cholera, filmAdaptationReleaseYear, 2007]
-
A.
filmReleaseYear
Indicates the calendar year in which a film was first officially released to the public.
-
B.
adaptationReleaseYear
chosen
Indicates the year in which an adaptation of a work was released.
-
C.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
D.
yearOfPassage
Indicates the specific calendar year in which a law, bill, or formal measure was officially passed or enacted.
-
E.
filmDebut
Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac6956488190a5644cdd5b55684f |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa86065881909d477e26fdd84d45 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.