Triple
T4664440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rock Shelters of Bhimbetka |
E102810
|
entity |
| Predicate | numberOfPaintedShelters |
P58295
|
FINISHED |
| Object | about 400 |
—
|
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: about 400 | Statement: [Rock Shelters of Bhimbetka, numberOfPaintedShelters, about 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPaintedShelters Context triple: [Rock Shelters of Bhimbetka, numberOfPaintedShelters, about 400]
-
A.
hasShelters
Indicates that one entity provides, contains, or is associated with one or more shelters for another entity or purpose.
-
B.
numberOfTents
Indicates the quantity of tents associated with a given entity or context.
-
C.
numberOfHouses
Indicates the quantity of houses associated with a given entity or context.
-
D.
numberOfShoreEstablishmentsInvolved
Indicates the count of shore-based establishments that are involved in or associated with a particular event, operation, or context.
-
E.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd633aeba88190a8329ed022d685b6 |
completed | March 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69bd62126b0c81909ba3f21b21e30d54 |
completed | March 20, 2026, 3:04 p.m. |
| PDg | Predicate description generation | batch_69bd631328fc81909b28ae0a2a3ed9bb |
completed | March 20, 2026, 3:09 p.m. |
Created at: March 20, 2026, 1:15 p.m.