Triple
T32486849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Polynesians |
E830265
|
entity |
| Predicate | canHoldCitizenshipOf |
P36272
|
FINISHED |
| Object | Polynesian states and territories |
—
|
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: Polynesian states and territories | Statement: [European Polynesians, canHoldCitizenshipOf, Polynesian states and territories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canHoldCitizenshipOf Context triple: [European Polynesians, canHoldCitizenshipOf, Polynesian states and territories]
-
A.
mayHoldCitizenshipOf
chosen
Indicates that an entity is allowed or eligible to possess citizenship status of a specified country or jurisdiction.
-
B.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
C.
hasTypicalCitizenship
Indicates that an entity is generally or commonly a citizen of a specified country or jurisdiction.
-
D.
possibleCountryOfCitizenship
Indicates that an entity could plausibly be a country in which the person or agent may hold, or be eligible to hold, citizenship.
-
E.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
- 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c3f9344c8190b18188da2feef2d8 |
completed | May 3, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:58 a.m.