Triple
T7795805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madurai Meenakshi Amman Temple |
E180294
|
entity |
| Predicate | hasSculpturesDepicting |
P23770
|
FINISHED |
| Object | Hindu deities |
—
|
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: Hindu deities | Statement: [Madurai Meenakshi Amman Temple, hasSculpturesDepicting, Hindu deities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSculpturesDepicting Context triple: [Madurai Meenakshi Amman Temple, hasSculpturesDepicting, Hindu deities]
-
A.
hasSculptureType
Indicates that an entity is associated with a sculpture and specifies the type or category of that sculpture.
-
B.
notableSculpture
Indicates that an entity is a sculpture for which the subject is especially known or recognized.
-
C.
completionOfSculptures
Indicates that one entity is responsible for finishing or bringing to completion the creation or production of sculptures associated with another entity.
-
D.
featuresSculptureOf
chosen
Indicates that one entity includes or displays a sculpture that depicts or represents another entity.
-
E.
numberOfSculptures
Indicates the quantity of sculptures associated with a given entity or context.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:31 p.m.