Triple
T7436313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lover (1992 film) |
E171623
|
entity |
| Predicate | sourceWorkAuthorNationality |
P6689
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [The Lover (1992 film), sourceWorkAuthorNationality, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sourceWorkAuthorNationality Context triple: [The Lover (1992 film), sourceWorkAuthorNationality, French]
-
A.
authorNationality
chosen
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
B.
creatorNationality
Indicates that the creator of an entity has a specified national affiliation or citizenship.
-
C.
coAuthorNationality
Indicates that two or more co-authors of a work share the same nationality or have nationalities being related in the context of their co-authorship.
-
D.
workOfAuthorOf
Indicates that one entity is a work (such as a book, article, or artwork) created by the author associated with another entity.
-
E.
authorOrigin
Indicates that an author has a specific place, region, or country as their origin or background.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.