Triple
T11793026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sri Sita Ramachandra Swamy Temple |
E280433
|
entity |
| Predicate | hasSanctumOrientation |
P12663
|
FINISHED |
| Object | facing east |
—
|
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: facing east | Statement: [Sri Sita Ramachandra Swamy Temple, hasSanctumOrientation, facing east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSanctumOrientation Context triple: [Sri Sita Ramachandra Swamy Temple, hasSanctumOrientation, facing east]
-
A.
hasOrientation
chosen
Indicates that one entity is positioned or directed in a specific spatial or conceptual alignment relative to a reference frame or another entity.
-
B.
hasPolicyOrientation
Indicates that one entity (such as an organization, document, or actor) is characterized by or aligned with a particular policy stance, direction, or focus.
-
C.
hasFieldOrientation
Indicates that one entity has a specified directional or spatial orientation relative to a field (such as magnetic, electric, or visual field).
-
D.
hasRegionalOrientation
Indicates that an entity is oriented toward, focused on, or primarily associated with a specific geographic region.
-
E.
hasFlukeOrientation
Indicates the orientation or positioning of a fluke relative to another reference object or axis.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5a082d08190a42541396a06ed98 |
completed | April 10, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69d8a2491f048190853239bc05090bf4 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.