Triple
T10406464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pusa, Bihar |
E245274
|
entity |
| Predicate | agriculturalFocus |
P93731
|
FINISHED |
| Object | crop research |
—
|
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: crop research | Statement: [Pusa, Bihar, agriculturalFocus, crop research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agriculturalFocus Context triple: [Pusa, Bihar, agriculturalFocus, crop research]
-
A.
agricultureUse
Indicates that something is used for, involved in, or designated for agricultural activities or purposes.
-
B.
usedAgriculture
Indicates that an entity employed agricultural methods, practices, or resources for cultivation, production, or related purposes.
-
C.
agriculturalPractice
Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
-
D.
agriculturalRole
Indicates a role or function that an entity has within agricultural activities, production, or systems.
-
E.
agriculturalImpact
Indicates the effect that an action, condition, or entity has on agricultural systems, productivity, or practices.
- F. None of above. chosen
Provenance (4 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9f834288190a0df246974ffaea8 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
| PDg | Predicate description generation | batch_69d4e944fac4819093b0312aa0efd729 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 12:08 p.m.