Triple
T21478419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amarnath Yatra route |
E529921
|
entity |
| Predicate | pilgrimDemographic |
P57386
|
FINISHED |
| Object | devotees of Shiva from across India |
—
|
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: devotees of Shiva from across India | Statement: [Amarnath Yatra route, pilgrimDemographic, devotees of Shiva from across India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pilgrimDemographic Context triple: [Amarnath Yatra route, pilgrimDemographic, devotees of Shiva from across India]
-
A.
primaryPilgrims
Indicates that the referenced entities are the main or principal participants undertaking a pilgrimage in relation to something or someone.
-
B.
pilgrimsPerYearApprox
Indicates an approximate number of pilgrims who travel to a place within a year.
-
C.
pilgrimsFrom
chosen
Indicates that one or more pilgrims originate from, or are associated with coming from, a particular place.
-
D.
pilgrimIdentity
Indicates that an entity is identified as a pilgrim, typically in the context of undertaking or being associated with a religious or spiritual journey.
-
E.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1951fc8190910f634327aa5c3f |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:20 p.m.