Triple
T13430244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohatta Palace |
E313587
|
entity |
| Predicate | hasChhatri |
P109896
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mohatta Palace, hasChhatri, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChhatri Context triple: [Mohatta Palace, hasChhatri, true]
-
A.
hasGhat
Indicates that a place or location possesses or is associated with a ghat (a series of steps or landing area leading to a body of water).
-
B.
hasRatha
Indicates that one entity possesses, includes, or is associated with a chariot (ratha) as part of its attributes or composition.
-
C.
hasGhatCount
Indicates the number of ghats associated with a given entity.
-
D.
hasChant
Indicates that an entity is associated with or characterized by a particular chant.
-
E.
isPancharangaKshetram
Indicates that a temple or sacred site is recognized as one of the Pancharanga Kshetrams, the five traditional holy shrines dedicated to Lord Ranganatha (Vishnu) along the Kaveri river.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed304ac8190a8021f749de8164c |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:40 p.m.