Triple
T4184574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanctuary of Our Lady of Lourdes |
E88278
|
entity |
| Predicate | pilgrimsPerYear |
P45240
|
FINISHED |
| Object | approximately 4 to 6 million |
—
|
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: approximately 4 to 6 million | Statement: [Sanctuary of Our Lady of Lourdes, pilgrimsPerYear, approximately 4 to 6 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pilgrimsPerYear Context triple: [Sanctuary of Our Lady of Lourdes, pilgrimsPerYear, approximately 4 to 6 million]
-
A.
pilgrimsPerYearApprox
chosen
Indicates an approximate number of pilgrims who travel to a place within a year.
-
B.
pilgrimageFrequency
Indicates how often an entity undertakes or participates in a pilgrimage.
-
C.
pilgrimageSeason
Indicates the time period or season during which religious pilgrimages customarily take place.
-
D.
primaryPilgrims
Indicates that the referenced entities are the main or principal participants undertaking a pilgrimage in relation to something or someone.
-
E.
numberOfPilgrimagesToMecca
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:45 p.m.