Triple
T25587003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thiruvambady Sri Krishna Temple |
E641412
|
entity |
| Predicate | localLanguageOfWorship |
P3115
|
FINISHED |
| Object | Malayalam |
—
|
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: Malayalam | Statement: [Thiruvambady Sri Krishna Temple, localLanguageOfWorship, Malayalam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localLanguageOfWorship Context triple: [Thiruvambady Sri Krishna Temple, localLanguageOfWorship, Malayalam]
-
A.
languageOfWorship
chosen
Indicates the language in which religious worship, rituals, or liturgical practices are conducted.
-
B.
languageOfDevotees
Indicates the language commonly used or spoken by a group of devotees in their religious or devotional practices.
-
C.
majorRegionOfWorship
Indicates the primary geographic region where a deity, religion, or cult is predominantly worshipped.
-
D.
dominantLocalLanguage
Indicates that one language is the primary or most widely used language within a specific local area or community.
-
E.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
- 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f96a44bc8190a38439dbc297ebc5 |
completed | May 2, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 4:17 p.m.