Triple
T34342994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Bean |
E881347
|
entity |
| Predicate | nationalityInPlay |
P193899
|
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: [Christopher Bean, nationalityInPlay, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityInPlay Context triple: [Christopher Bean, nationalityInPlay, American]
-
A.
nationalityInWorld
Indicates that an entity has a specific national affiliation or citizenship within the world context.
-
B.
nationalityRepresented
Indicates the country or nation that an entity officially represents, typically in a professional, competitive, or diplomatic capacity.
-
C.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
D.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
-
E.
includedNationality
Indicates that one entity’s set of nationalities contains or encompasses the nationality of another entity.
- F. None of above. chosen
Provenance (4 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_69f349bc55e881908c8e338ef76b0043 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
| PDg | Predicate description generation | batch_69fd592cc56081908ce456114d407616 |
completed | May 8, 2026, 3:31 a.m. |
Created at: May 1, 2026, 1:58 a.m.