Triple
T24874849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laxminarayan Temple |
E622538
|
entity |
| Predicate | muralThemes |
P120414
|
FINISHED |
| Object | Krishna legends |
—
|
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: Krishna legends | Statement: [Laxminarayan Temple, muralThemes, Krishna legends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: muralThemes Context triple: [Laxminarayan Temple, muralThemes, Krishna legends]
-
A.
muralsStyle
Indicates that one entity is a mural whose artistic style or aesthetic is characterized by, derived from, or associated with the other entity.
-
B.
muralColor
Indicates that a mural has a specific color or set of colors.
-
C.
notableMural
Indicates that an entity is a mural distinguished by particular significance, prominence, or recognition.
-
D.
hasMuralsDepicting
chosen
Indicates that one entity contains or features murals that visually represent or portray another entity.
-
E.
hasMuralsFrom
Indicates that a location or structure contains murals that originate from or were created in a specified place or time period.
- 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_69e2fac3fdbc81909c2ec49be5743cd9 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 5:23 a.m.