Triple
T15870531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Thumper |
E384817
|
entity |
| Predicate | personReferredToNationality |
P78054
|
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: [The Thumper, personReferredToNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personReferredToNationality Context triple: [The Thumper, personReferredToNationality, American]
-
A.
nationalityOfPersonReferredTo
chosen
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
B.
userNationality
Indicates that a user has a specific national affiliation or citizenship.
-
C.
namedForNationality
Indicates that something is named after or in reference to a particular nationality or national identity.
-
D.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
E.
describesNationality
Indicates that one entity specifies the national identity or citizenship associated with another entity.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:50 a.m.