Triple
T2680094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French overseas territories |
E56552
|
entity |
| Predicate | grantCitizenship |
P4308
|
FINISHED |
| Object | French citizenship |
—
|
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 citizenship | Statement: [French overseas territories, grantCitizenship, French citizenship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantCitizenship Context triple: [French overseas territories, grantCitizenship, French citizenship]
-
A.
acquireCitizenshipBy
chosen
Indicates the process or means by which an entity obtains or is granted citizenship through a specific method, action, or legal basis.
-
B.
laterCitizenship
Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
-
C.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
D.
citizenshipGrantedYear
Indicates the specific year in which an entity was officially granted citizenship.
-
E.
mayHoldCitizenshipOf
Indicates that an entity is allowed or eligible to possess citizenship status of a specified country or jurisdiction.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.