Triple
T31928778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pandav Leni |
E815185
|
entity |
| Predicate | hasInscriptionsScript |
P200148
|
FINISHED |
| Object | Brahmi script |
—
|
NE NERFINISHED |
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: Brahmi script | Statement: [Pandav Leni, hasInscriptionsScript, Brahmi script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInscriptionsScript Context triple: [Pandav Leni, hasInscriptionsScript, Brahmi script]
-
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.
hasInscriptionsCalled
Indicates that an entity bears inscriptions that are referred to or named by a specific designation.
-
D.
hasTypeOfInscriptions
Indicates that an entity bears or is associated with a specific kind or category of inscriptions.
-
E.
mayBeInscribedAs
Indicates that one entity is permitted or suitable to be formally recorded, written, or engraved as another entity.
- 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_69f348f1df848190851bbfb988da3414 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff779e3f0c8190a861f1e4000fd9d9 |
completed | May 9, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69ff77202638819086e4b9f9c0bc7b31 |
completed | May 9, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69ff779d3d788190af5a2dbc4d7ca3c8 |
completed | May 9, 2026, 6:06 p.m. |
Created at: May 1, 2026, 12:04 a.m.