Triple
T32285710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faces Places |
E824821
|
entity |
| Predicate | directorBirthPlaceOfAgnèsVarda |
P90944
|
FINISHED |
| Object | Belgium |
—
|
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: Belgium | Statement: [Faces Places, directorBirthPlaceOfAgnèsVarda, Belgium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: directorBirthPlaceOfAgnèsVarda Context triple: [Faces Places, directorBirthPlaceOfAgnèsVarda, Belgium]
-
A.
creatorLivedIn
Indicates that the person who created a work resided in a particular place for some period of time.
-
B.
creatorPlaceOfBirth
chosen
Indicates that the place specified is the location where the creator of an entity was born.
-
C.
placeOfBirth
Indicates the location where a person or other entity was born.
-
D.
locatedInMetropolitanFrance
Indicates that the subject is geographically situated within the territory of metropolitan (continental) France.
-
E.
directorResidenceAtTimeOfProduction
Indicates that a director resided at a particular location during the time a specific production was being made.
- 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_69f349101b788190b4f14884dc7d1ed2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
Created at: May 1, 2026, 12:43 a.m.