Triple
T14452477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jagat Mandir |
E358369
|
entity |
| Predicate | hasFlagOnShikhara |
P114337
|
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: [Jagat Mandir, hasFlagOnShikhara, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlagOnShikhara Context triple: [Jagat Mandir, hasFlagOnShikhara, true]
-
A.
hasChhatri
Indicates that one entity possesses or features a chhatri (a dome-shaped pavilion or canopy structure) in relation to another entity or location.
-
B.
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).
-
C.
hasRatha
Indicates that one entity possesses, includes, or is associated with a chariot (ratha) as part of its attributes or composition.
-
D.
hasGhatCount
Indicates the number of ghats associated with a given entity.
-
E.
hasFlagstaff
Indicates that one entity possesses, contains, or is equipped with a flagstaff (a pole or staff for displaying a flag).
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de916244948190bb09d1bfc485ba50 |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:19 a.m.