Triple
T23328615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiat BR series |
E591375
|
entity |
| Predicate | geographicRegionOfUse |
P150084
|
FINISHED |
| Object | Mediterranean theatre |
—
|
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 theatre | Statement: [Fiat BR series, geographicRegionOfUse, Mediterranean theatre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicRegionOfUse Context triple: [Fiat BR series, geographicRegionOfUse, Mediterranean theatre]
-
A.
geographicalUsage
chosen
Indicates that something is used, applied, or occurs within a particular geographic area or region.
-
B.
countryOrRegionUsed
Indicates that something is used within, or applies to, a specific country or geographic region.
-
C.
geographicalRegionType
Indicates the specific kind or category of geographical region that an entity belongs to (e.g., continent, country, province, or city).
-
D.
marketRegion
Indicates the geographic or demographic area in which a product, service, or entity is actively marketed or targeted.
-
E.
usedInCountryOrRegion
Indicates that something (such as an item, concept, or practice) is utilized or applied within a specified country or region.
- 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_69e25d1effe4819096907f95f610dbff |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f197eb6cd481908acd5619b3af246d |
completed | April 29, 2026, 5:32 a.m. |
| PD | Predicate disambiguation | batch_69effcf8ca2c8190887d4f4656617d21 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:13 p.m.