Triple
T34873675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Day |
E1005819
|
entity |
| Predicate | hasTypicalBearerNationality |
P79483
|
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: [William Day, hasTypicalBearerNationality, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalBearerNationality Context triple: [William Day, hasTypicalBearerNationality, British]
-
A.
typicalBearersNationality
chosen
Indicates the nationality that entities of a given type or class are most commonly associated with.
-
B.
hasTypicalCitizenship
Indicates that an entity is generally or commonly a citizen of a specified country or jurisdiction.
-
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.
hasOwnerNationalityStereotype
Indicates that an entity is associated with a stereotype about the nationality of its owner.
- 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_69f76dbde1c08190a24e7f9beb564c8d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff45793d5c81909dc503ad1f714ee2 |
completed | May 9, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69ff41cb0e088190a6e9b03cb20e5fad |
completed | May 9, 2026, 2:16 p.m. |
Created at: May 3, 2026, 4 p.m.