Triple
T4646643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pithla Bhakri |
E102187
|
entity |
| Predicate | typicalConsumers |
P10804
|
FINISHED |
| Object | rural communities in Maharashtra |
—
|
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: rural communities in Maharashtra | Statement: [Pithla Bhakri, typicalConsumers, rural communities in Maharashtra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalConsumers Context triple: [Pithla Bhakri, typicalConsumers, rural communities in Maharashtra]
-
A.
typicalAudience
chosen
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
D.
traditionalUsers
Indicates that the associated users adhere to long-established or customary practices, methods, or preferences in the given context.
-
E.
typicalConsumptionAge
Indicates the age at which something is most commonly or normally consumed.
- 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6632708c8190b627d99363ab062c |
completed | March 20, 2026, 3:22 p.m. |
| PD | Predicate disambiguation | batch_69bd620fc5e081908325ac8e6a6384ab |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:14 p.m.