Triple
T12770791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nandgaon |
E305241
|
entity |
| Predicate | hasTopographyFeature |
P940
|
FINISHED |
| Object | hilltop temple complex |
—
|
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: hilltop temple complex | Statement: [Nandgaon, hasTopographyFeature, hilltop temple complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTopographyFeature Context triple: [Nandgaon, hasTopographyFeature, hilltop temple complex]
-
A.
hasTopographicContext
Indicates that one entity is related to or characterized by a particular topographic or physical landscape context.
-
B.
topographyBasedOn
Indicates that the topographical characteristics of one entity are derived from, determined by, or modeled using the topography of another entity.
-
C.
hasLandform
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
D.
topographicalCategory
Indicates the type of landform or surface feature that characterizes the physical terrain associated with an entity.
-
E.
hasElevationFeature
Indicates that one entity possesses or is characterized by a particular elevation-related feature or attribute, such as height, altitude, or vertical relief.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df4b36c81909bcc913dd5e535f8 |
completed | April 10, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.