Triple
T25525026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaikasi Visakam |
E639751
|
entity |
| Predicate | majorRegionOfObservance |
P32975
|
FINISHED |
| Object | Tamil Nadu |
—
|
NE NERFINISHED |
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: Tamil Nadu | Statement: [Vaikasi Visakam, majorRegionOfObservance, Tamil Nadu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorRegionOfObservance Context triple: [Vaikasi Visakam, majorRegionOfObservance, Tamil Nadu]
-
A.
missionRegion
Indicates the geographic or administrative region in which a mission is carried out or assigned.
-
B.
observesRegion
Indicates that an entity monitors, watches, or collects information about a specific geographic or spatial region.
-
C.
mainlyObservedIn
Indicates that something occurs, appears, or is found predominantly within a particular context, location, group, or condition.
-
D.
hasMajorRegionOfAdherents
Indicates that a belief system, organization, or movement has a significant concentration of its adherents located in a particular geographic region.
-
E.
isMajorRegionFor
chosen
Indicates that a region serves as a primary or significant area associated with a particular entity, activity, or phenomenon.
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 21, 2026, 3:09 p.m.