Triple
T23911803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taravai |
E601957
|
entity |
| Predicate | inceptionCountryStatus |
P18803
|
FINISHED |
| Object | French overseas territory |
—
|
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: French overseas territory | Statement: [Taravai, inceptionCountryStatus, French overseas territory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inceptionCountryStatus Context triple: [Taravai, inceptionCountryStatus, French overseas territory]
-
A.
countryStatus
chosen
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
B.
endedInCountry
Indicates that an event, process, or entity’s existence or occurrence concluded within the boundaries of a specified country.
-
C.
appearsInWorkCountryOfOrigin
Indicates that an entity appears in a work whose country of origin is the specified country.
-
D.
productionCountries
Indicates the countries where a work (such as a film or TV show) was produced or financed.
-
E.
countryOf
Indicates that one entity is the country to which another entity belongs, is located in, or is associated with.
- 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_69e2953a187081908346a9f36e85fc98 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ce95f4848190b98339d8a6c988ba |
completed | April 29, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:38 p.m.