Triple
T25072734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panchganga River |
E627960
|
entity |
| Predicate | hasConfluencePointAt |
P174216
|
FINISHED |
| Object | Prayag Chikhali near Kolhapur |
—
|
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: Prayag Chikhali near Kolhapur | Statement: [Panchganga River, hasConfluencePointAt, Prayag Chikhali near Kolhapur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConfluencePointAt Context triple: [Panchganga River, hasConfluencePointAt, Prayag Chikhali near Kolhapur]
-
A.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
B.
containsPoint
Indicates that a geometric region or shape includes a given point within its boundaries.
-
C.
isReferencePointFor
Indicates that one entity serves as a positional or conceptual basis used to locate, measure, or interpret another entity.
-
D.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
E.
hasNearbyCrossingPoint
Indicates that one location has a crossing point (such as a bridge, crosswalk, or intersection) situated close to it.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69f6bbf5a8288190ae170bcbe8ab65cf |
completed | May 3, 2026, 3:07 a.m. |
Created at: April 18, 2026, 6:19 a.m.