Triple
T7202131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gonesse |
E168772
|
entity |
| Predicate | regionHistoricallyKnownFor |
P67817
|
FINISHED |
| Object | grain cultivation |
—
|
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: grain cultivation | Statement: [Gonesse, regionHistoricallyKnownFor, grain cultivation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionHistoricallyKnownFor Context triple: [Gonesse, regionHistoricallyKnownFor, grain cultivation]
-
A.
traditionallyKnownFor
chosen
Indicates that something is widely and historically recognized or reputed for a particular characteristic, activity, product, or role.
-
B.
regionallyKnownAs
Indicates that an entity is known by a particular name or designation within a specific geographic region.
-
C.
historicallyPopularIn
Indicates that something was notably popular or widely favored within a particular place or context during a past historical period.
-
D.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
E.
historicallyBasedIn
Indicates that one entity is located in or associated with a place as its base of operations during a specific historical period.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e94a9ee4819086de79fcdfa1836a |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:52 p.m.