Triple
T34654708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Jeune Homme et la Mort |
E889939
|
entity |
| Predicate | scenarioWriterNationality |
P179574
|
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: [Le Jeune Homme et la Mort, scenarioWriterNationality, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenarioWriterNationality Context triple: [Le Jeune Homme et la Mort, scenarioWriterNationality, French]
-
A.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
B.
createdByNationality
Indicates that something was created by an individual or group belonging to a specified nationality.
-
C.
builderNationality
Indicates the country or national affiliation of the entity that built or constructed another entity.
-
D.
creatorNationality
Indicates that the creator of an entity has a specified national affiliation or citizenship.
-
E.
authorNationality
Indicates the relationship between an author and the country or nationality with which that author is identified.
- 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_69f349d906bc8190b2efd9eff237d94b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f722c73a9081908d817e2b0b3f19a2 |
completed | May 3, 2026, 10:26 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f7221bc57c819085c1464a45e61b2f |
completed | May 3, 2026, 10:23 a.m. |
Created at: May 1, 2026, 2:04 a.m.