Triple
T27467065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaultier |
E693202
|
entity |
| Predicate | hasSurnameUsageRegion |
P119132
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Gaultier, hasSurnameUsageRegion, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurnameUsageRegion Context triple: [Gaultier, hasSurnameUsageRegion, France]
-
A.
hasSurnameRegionAssociation
chosen
Indicates that there is a relationship between a surname and a geographic region, such as origin, prevalence, or cultural association.
-
B.
usedAsSurnameInCountry
Indicates that a particular name functions as a family surname within the specified country.
-
C.
hasNameUsageCountry
Indicates that a particular name is used or recognized within a specified country.
-
D.
possibleSurnameUsage
Indicates that an entity can potentially be used or recognized as a surname for another entity.
-
E.
givenNameUsageCountry
Indicates the country in which a particular given name is used or commonly found.
- 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_69ef538105548190a771cc5a0cf8c211 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: April 27, 2026, 12:52 p.m.