Triple
T7103524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brionnais |
E165516
|
entity |
| Predicate | hasPrimaryUseOfLand |
P14072
|
FINISHED |
| Object | pasture |
—
|
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: pasture | Statement: [Brionnais, hasPrimaryUseOfLand, pasture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryUseOfLand Context triple: [Brionnais, hasPrimaryUseOfLand, pasture]
-
A.
primaryLandUse
chosen
Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
-
B.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
C.
hasMainEconomicUse
Indicates that something serves as the primary or principal economic function, purpose, or use of another entity.
-
D.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
E.
formerLandUse
Indicates the type of land use that characterized a location prior to its current or present use.
- 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_69c6887fcddc8190a5d58908f6dee590 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e58a0a2c819088e0c8874fb4491f |
completed | March 27, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c313e481908b61a23fc89f9332 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:42 p.m.