Triple
T18836407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pashupatinath Temple, Mandsaur |
E460675
|
entity |
| Predicate | lingamFacesCount |
P78259
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Pashupatinath Temple, Mandsaur, lingamFacesCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lingamFacesCount Context triple: [Pashupatinath Temple, Mandsaur, lingamFacesCount, 8]
-
A.
lingamType
Indicates the specific type or classification of a lingam in the relationship or context being modeled.
-
B.
numberOfFaces
chosen
Indicates the relationship that specifies how many faces a given object or entity has.
-
C.
numberOfAvatarsDescribed
Indicates the count of distinct avatars that are described in a given context or data record.
-
D.
hasLinga
Indicates a relationship where an entity possesses or is associated with a linga (a symbolic representation, typically of Shiva).
-
E.
numberOfColossalHeads
Indicates the quantity of colossal heads associated with or attributed to a given subject.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a99e86388190957acaaab401b5cb |
completed | April 20, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d1e7dac81909ea1e758c87773c5 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:56 a.m.