Triple
T28452854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Brugeoise wooden cars |
E716624
|
entity |
| Predicate | notableCountryOfOperation |
P6230
|
FINISHED |
| Object | Argentina |
—
|
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: Argentina | Statement: [La Brugeoise wooden cars, notableCountryOfOperation, Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCountryOfOperation Context triple: [La Brugeoise wooden cars, notableCountryOfOperation, Argentina]
-
A.
operatesInCountries
Indicates that an entity conducts its activities or business within the specified countries.
-
B.
notableUseCountry
Indicates that something is notably or prominently used within a particular country.
-
C.
operatedByCountry
Indicates that an entity (such as an organization, facility, or service) is run, managed, or controlled by a specific country or its government.
-
D.
notableCountry
chosen
Indicates that a country holds particular significance or prominence in relation to the subject entity.
-
E.
notableHolderCountry
Indicates that a country is recognized as a significant or notable holder of a particular item, title, record, or distinction.
- 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_69efd6b76f8c8190a7ba908aca280942 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a011c64ff18819099195701bbecbb20 |
completed | May 11, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_6a011b7f7a508190b2ebb518fb7a2fe9 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 28, 2026, 1:52 a.m.