Triple
T35548798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Adoptés |
E1027294
|
entity |
| Predicate | filmmakingRoleOfMélanieLaurent |
P136019
|
FINISHED |
| Object | director |
—
|
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: director | Statement: [Les Adoptés, filmmakingRoleOfMélanieLaurent, director]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmmakingRoleOfMélanieLaurent Context triple: [Les Adoptés, filmmakingRoleOfMélanieLaurent, director]
-
A.
cinematicRole
Indicates that one entity performs or holds a specific role or character part within a cinematic work associated with another entity.
-
B.
roleInFilmProduction
chosen
Indicates the specific function or responsibility an entity has within the making of a film.
-
C.
roleInFilmEcosystem
Indicates the specific function or position an entity holds within the broader network of activities, stakeholders, and processes that make up the film ecosystem.
-
D.
hasBrigitteBardotRoleType
Indicates that an entity has a role type specifically associated with Brigitte Bardot (e.g., portraying her or a role category defined in relation to her).
-
E.
workedOnFilmReleasedBy
Indicates that one entity contributed work to a film that was distributed or released by another entity.
- 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_69f76e008ba08190927acd8e5e0344c8 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.