Triple
T2197849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trimbakeshwar |
E50416
|
entity |
| Predicate | architectureMaterial |
P618
|
FINISHED |
| Object | Black stone |
—
|
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: Black stone | Statement: [Trimbakeshwar, architectureMaterial, Black stone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: architectureMaterial Context triple: [Trimbakeshwar, architectureMaterial, Black stone]
-
A.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
B.
wallMaterial
Indicates that one entity is the material from which a wall or walls of another entity are constructed.
-
C.
material
chosen
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
D.
exteriorMaterial
Indicates the material that forms the outer surface or outer construction of an object or structure.
-
E.
constructionType
Indicates the specific method or style by which something is built or constructed.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbf79f3e08190b56e9d7c0ff27237 |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.