Triple
T34069776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muktagiri |
E873730
|
entity |
| Predicate | hasTempleNumbering |
P195652
|
FINISHED |
| Object | temples numbered sequentially |
—
|
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: temples numbered sequentially | Statement: [Muktagiri, hasTempleNumbering, temples numbered sequentially]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTempleNumbering Context triple: [Muktagiri, hasTempleNumbering, temples numbered sequentially]
-
A.
isNumberedTempleOf
Indicates that one entity is a specific, designated temple identified by a particular number within a series or system associated with another entity.
-
B.
hasTempleCount
Indicates that an entity is associated with a specified number of temples.
-
C.
hasTempleOf
Indicates that a location or entity possesses, contains, or is the site of a temple dedicated to a particular deity, figure, or purpose.
-
D.
templeNumberByDedication
Indicates the numerical identifier assigned to a temple based on its specific dedication (e.g., to a deity, saint, or sacred figure).
-
E.
hasTempleCode
Indicates that an entity is associated with a specific temple identification code.
- 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_69f349a566808190a1c63b898f33cddf |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
| PDg | Predicate description generation | batch_69fddd364c1481908794c9d423bdc2d7 |
completed | May 8, 2026, 12:55 p.m. |
Created at: May 1, 2026, 1:52 a.m.