Triple
T21252807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hinglaj Mata Temple |
E523786
|
entity |
| Predicate | estimatedPilgrimsPerYear |
P45240
|
FINISHED |
| Object | tens of thousands |
—
|
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: tens of thousands | Statement: [Hinglaj Mata Temple, estimatedPilgrimsPerYear, tens of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedPilgrimsPerYear Context triple: [Hinglaj Mata Temple, estimatedPilgrimsPerYear, tens of thousands]
-
A.
pilgrimsPerYearApprox
chosen
Indicates an approximate number of pilgrims who travel to a place within a year.
-
B.
pilgrimsPerDay
Indicates the number of pilgrims associated with a place, route, or event during a single day.
-
C.
pilgrimsPerDayOnPeakDays
Indicates the number of pilgrims present or arriving each day during the busiest or peak pilgrimage days.
-
D.
pilgrimFootfall
Indicates the occurrence or trace of a pilgrim’s steps or movement along a path or at a specific place.
-
E.
hasPilgrims
Indicates that an entity is associated with or contains pilgrims, typically as visitors, members, or participants in a pilgrimage.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359f5b408190b951adddba83c97a |
completed | April 21, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:57 p.m.