Triple
T24295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard |
E482
|
entity |
| Predicate | associatedWithNationalityOfNameBearer |
P2
|
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: [Howard, associatedWithNationalityOfNameBearer, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithNationalityOfNameBearer Context triple: [Howard, associatedWithNationalityOfNameBearer, American]
-
A.
nationalityRepresented
Indicates the country or nation that an entity officially represents, typically in a professional, competitive, or diplomatic capacity.
-
B.
countryOfCitizenship
chosen
Indicates the country in which a person or entity holds legal citizenship.
-
C.
countryJoined
Indicates that a country became a member of, or formally entered into, a specific organization, union, alliance, or agreement.
-
D.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
-
E.
relatedCountry
Indicates that there is a relevant or associated relationship between an entity and a specified country, without specifying the exact nature of that relationship.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.