Triple
T4924897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaney |
E110553
|
entity |
| Predicate | associatedWithNationalityOfBearer |
P33828
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Chaney, associatedWithNationalityOfBearer, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithNationalityOfBearer Context triple: [Chaney, associatedWithNationalityOfBearer, American]
-
A.
associatedWithNotableBearerNationality
Indicates that an entity is connected to the nationality of a notable bearer of a related name or title.
-
B.
associatedWithNationality
chosen
Indicates that one entity has a connection or affiliation with the nationality of another entity.
-
C.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
-
D.
notableBearerNationality
Indicates that the subject has a notable bearer whose nationality is the specified object.
-
E.
namedAfterCountryOfCitizenship
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_69bd4413f9908190afcff44d7929cc4c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffeb86c8190a2fabe1ae1d54118 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3695c8819094e7ad2f6d4ba1ac |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.