Triple
T25083118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barataria |
E628237
|
entity |
| Predicate | hasGeographicalStyle |
P62295
|
FINISHED |
| Object | Mediterranean-style |
—
|
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: Mediterranean-style | Statement: [Barataria, hasGeographicalStyle, Mediterranean-style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeographicalStyle Context triple: [Barataria, hasGeographicalStyle, Mediterranean-style]
-
A.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
-
B.
hasGeographyCharacteristic
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
C.
hasGeographicalDirection
Indicates that one entity is oriented, located, or extends in a specific cardinal or intercardinal direction relative to another entity.
-
D.
containsGeographicalArea
Indicates that one geographical area spatially encompasses or includes another geographical area within its boundaries.
-
E.
usesRegionalStyle
chosen
Indicates that one entity employs or applies a style, method, or convention characteristic of a particular geographic region in relation to another entity or context.
- 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_69e2ff2e73f881909992bf3eda5c25cb |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 18, 2026, 6:22 a.m.