Triple
T34569592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franc Noir de la Haute-Saône |
E887587
|
entity |
| Predicate | historicalCultivationCountry |
P56227
|
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: [Franc Noir de la Haute-Saône, historicalCultivationCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalCultivationCountry Context triple: [Franc Noir de la Haute-Saône, historicalCultivationCountry, France]
-
A.
historicalCultivation
Indicates that an entity has been traditionally grown, farmed, or otherwise cultivated in relation to another entity over a significant historical period.
-
B.
cultivatedInCountry
chosen
Indicates that something (such as a crop, plant, or organism) is grown or produced through cultivation within the specified country.
-
C.
historicalOriginCountry
Indicates the country from which something originally came or first emerged in a historical context.
-
D.
widelyCultivatedIn
Indicates that something is grown extensively or on a large scale within a particular place or region.
-
E.
cultivatedInContinent
Indicates that something (typically a crop or organism) is grown or cultivated within the geographic boundaries of a specified continent.
- 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_69f349d1a5fc81908557a46875b2f157 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a00776c4ebc8190899005fda34234d5 |
completed | May 10, 2026, 12:17 p.m. |
| PD | Predicate disambiguation | batch_6a0076f8a4c4819093ed577e67aa38f9 |
completed | May 10, 2026, 12:15 p.m. |
Created at: May 1, 2026, 2:02 a.m.