Triple
T18555998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganesha Ratha |
E453503
|
entity |
| Predicate | templePlanType |
P18959
|
FINISHED |
| Object | ratha-type temple |
—
|
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: ratha-type temple | Statement: [Ganesha Ratha, templePlanType, ratha-type temple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: templePlanType Context triple: [Ganesha Ratha, templePlanType, ratha-type temple]
-
A.
templeType
chosen
Indicates the specific category or classification of a temple in terms of its form, function, or religious/architectural style.
-
B.
mainTemple
Indicates that one entity serves as the primary or central temple associated with another entity.
-
C.
templeMaterial
Indicates that a temple is constructed from, or primarily composed of, a specified material.
-
D.
templeName
Indicates that an entity is identified by or associated with the name of a temple.
-
E.
attributesTempleTo
Indicates that a particular temple is ascribed, assigned, or associated to a specific entity, such as a deity, person, group, or place.
- 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53806046481908efbbe6909b2c68b |
completed | April 19, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69e469e274a48190a570b25cfef4d890 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:38 a.m.