Triple
T2505185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cantal |
E52560
|
entity |
| Predicate | agriculturalSpecialty |
P25683
|
FINISHED |
| Object | beef cattle |
—
|
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: beef cattle | Statement: [Cantal, agriculturalSpecialty, beef cattle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agriculturalSpecialty Context triple: [Cantal, agriculturalSpecialty, beef cattle]
-
A.
agriculturalPractice
Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
-
B.
agriculturalRole
Indicates a role or function that an entity has within agricultural activities, production, or systems.
-
C.
farmingCharacteristics
Indicates the specific methods, practices, or attributes that characterize how farming is conducted in relation to an entity.
-
D.
hasAgriculturalProduction
chosen
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
E.
crop
Indicates the action of cutting or trimming part of an object or image, typically to remove unwanted outer areas while keeping a selected region.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.