Triple
T28488891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Cook |
E720906
|
entity |
| Predicate | namesakeCitizenship |
P4216
|
FINISHED |
| Object | British |
—
|
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: British | Statement: [Division of Cook, namesakeCitizenship, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namesakeCitizenship Context triple: [Division of Cook, namesakeCitizenship, British]
-
A.
namesakeNationality
Indicates that one entity has the same nationality as the person or entity after whom it is named.
-
B.
namesakeDescription
Indicates that the object provides a descriptive explanation of why or how the subject is considered a namesake of something or someone.
-
C.
namesakeFamily
Indicates that one entity is a family or familial group that shares the same name as, or is named after, another entity.
-
D.
namesakeStatus
Indicates that one entity serves as the namesake of another, or that two entities share a relationship based on having the same name.
-
E.
namedAfterCountryOfCitizenship
chosen
Indicates that something is named after the country where a person holds 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_69f01a5a47148190b0a7e111bc432e0a |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 3 a.m.