Triple
T5737572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magh Mela |
E126535
|
entity |
| Predicate | hasCrowdSize |
P18989
|
FINISHED |
| Object | hundreds of thousands of pilgrims |
—
|
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: hundreds of thousands of pilgrims | Statement: [Magh Mela, hasCrowdSize, hundreds of thousands of pilgrims]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrowdSize Context triple: [Magh Mela, hasCrowdSize, hundreds of thousands of pilgrims]
-
A.
hasCrowdLevel
chosen
Indicates the degree or intensity of how crowded a place, event, or situation is.
-
B.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
-
C.
crowdWas
Indicates that a crowd possessed or exhibited a particular state, quality, or condition.
-
D.
supportsAudienceSize
Indicates that one entity is capable of accommodating or handling an audience of a specified size.
-
E.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255c8c308190821f968ec41c5078 |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:47 p.m.