Triple
T34432792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chandragiri Hill |
E883871
|
entity |
| Predicate | hasInscriptionsFrom |
P201862
|
FINISHED |
| Object | 10th century |
—
|
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: 10th century | Statement: [Chandragiri Hill, hasInscriptionsFrom, 10th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInscriptionsFrom Context triple: [Chandragiri Hill, hasInscriptionsFrom, 10th century]
-
A.
hasInscriptions
Indicates that an object, surface, or artifact bears written, carved, or engraved inscriptions on it.
-
B.
hasInscriptionsFoundAt
Indicates that inscriptions associated with an entity have been discovered at a specified location.
-
C.
issuedInscriptionsIn
Indicates that an entity (such as an authority or issuer) produced or authorized inscriptions within a specified place or context.
-
D.
isInscribedOn
Indicates that text, symbols, or markings are written, carved, or otherwise permanently placed onto the surface of an object.
-
E.
numberOfInscriptions
Indicates the total count of inscriptions associated with a given entity or object.
- 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_69f349c3dd2c819092cc9e64809f4a42 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a002ae74da08190a4b47e0ff0f7f8fe |
completed | May 10, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_6a0029cc369c81909578e52c4a75ab18 |
completed | May 10, 2026, 6:46 a.m. |
| PDg | Predicate description generation | batch_6a002ae65e0c81909a5989dd73f027f5 |
completed | May 10, 2026, 6:51 a.m. |
Created at: May 1, 2026, 2 a.m.