Triple
T33347457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Jury Prize |
E853837
|
entity |
| Predicate | mayHaveLocalName |
P176523
|
FINISHED |
| Object | festival-specific title |
—
|
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: festival-specific title | Statement: [Special Jury Prize, mayHaveLocalName, festival-specific title]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveLocalName Context triple: [Special Jury Prize, mayHaveLocalName, festival-specific title]
-
A.
hasLocalName
Indicates that an entity is known by a specific name or designation within a particular local language, script, or regional context.
-
B.
hasLocalNameFor
Indicates that one entity serves as the local or context-specific name or label used to refer to another entity.
-
C.
hasNoWidelyUsedLocalName
Indicates that the entity does not have a commonly used or widely recognized name in the local language or region.
-
D.
notableLocalName
Indicates that an entity is known by a notable or commonly used local name within a specific region or community.
-
E.
modernLocalName
Indicates the current, locally used name or designation for an entity, as recognized in the present time.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6e312d7fc819094dec41810f2585d |
completed | May 3, 2026, 5:54 a.m. |
Created at: May 1, 2026, 1:34 a.m.