Triple
T37671498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Bossu (1959 film) |
E937968
|
entity |
| Predicate | adaptationOfWorkFromCountry |
P21186
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Le Bossu (1959 film), adaptationOfWorkFromCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationOfWorkFromCountry Context triple: [Le Bossu (1959 film), adaptationOfWorkFromCountry, France]
-
A.
nationalityInAdaptation
Indicates that an entity’s nationality, as portrayed in an adaptation, is specified or differs from its original source.
-
B.
adaptationCountry
chosen
Indicates the country in which an adaptation (such as a remake, translation, or localized version) of an original work is produced or set.
-
C.
televisionAdaptationCountry
Indicates the country in which a television adaptation of a work was produced or primarily created.
-
D.
adaptedWorkOf
Indicates that one work is derived from, based on, or reinterprets the content of another pre-existing work.
-
E.
collaboratedOnAdaptationOf
Indicates that two or more entities worked together on creating or producing an adaptation of an existing 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_69f76ed7b1408190ba8c93c53cb8becf |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.