Triple
T9953792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luigi’s Pizza |
E195394
|
entity |
| Predicate | hasOwnerNationalityStereotype |
P91341
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [Luigi’s Pizza, hasOwnerNationalityStereotype, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOwnerNationalityStereotype Context triple: [Luigi’s Pizza, hasOwnerNationalityStereotype, Italian]
-
A.
appliesToPersonNationality
Indicates that something is relevant or applicable specifically to a person’s nationality.
-
B.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
-
C.
riddenByNationality
Indicates that something being ridden (such as an animal or vehicle) is ridden by a rider of a specified nationality.
-
D.
hostNationality
Indicates the national affiliation or citizenship of the host in a given hosting relationship or context.
-
E.
hasHostCitizenship
Indicates that an entity holds citizenship in, or is a citizen of, a specified host country or jurisdiction.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb694b95481909d049302818e7137 |
completed | April 2, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:46 p.m.