Triple
T18534183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tirumala Venkateswara Temple |
E452918
|
entity |
| Predicate | pilgrimsPerDay |
P132038
|
FINISHED |
| Object | often over 50,000 |
—
|
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: often over 50,000 | Statement: [Tirumala Venkateswara Temple, pilgrimsPerDay, often over 50,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pilgrimsPerDay Context triple: [Tirumala Venkateswara Temple, pilgrimsPerDay, often over 50,000]
-
A.
pilgrimsPerYearApprox
Indicates an approximate number of pilgrims who travel to a place within a year.
-
B.
pilgrimFootfall
Indicates the occurrence or trace of a pilgrim’s steps or movement along a path or at a specific place.
-
C.
pilgrimageFrequency
Indicates how often an entity undertakes or participates in a pilgrimage.
-
D.
pilgrimageNumber
Indicates the number or count associated with a particular pilgrimage event or journey.
-
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. chosen
Provenance (4 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53400d548819080b17f30b3ee7174 |
completed | April 19, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2b93bc8190a6070018d7046547 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:37 a.m.