Triple
T2457044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lourdes apparitions of 1858 |
E54445
|
entity |
| Predicate | annualPilgrimsEstimate |
P12597
|
FINISHED |
| Object | millions |
—
|
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: millions | Statement: [Lourdes apparitions of 1858, annualPilgrimsEstimate, millions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: annualPilgrimsEstimate Context triple: [Lourdes apparitions of 1858, annualPilgrimsEstimate, millions]
-
A.
estimatedEmigrants
Indicates the estimated number of people who have left a place or country to live elsewhere.
-
B.
pilgrimageFrequency
Indicates how often an entity undertakes or participates in a pilgrimage.
-
C.
touristArrivalsPerYearApprox
chosen
Indicates an approximate count of how many tourists arrive at a place over the course of a year.
-
D.
numberOfPilgrimagesToMecca
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
-
E.
hasApproximateAdherents
Indicates that an entity is associated with a non-exact, estimated number of adherents or followers.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.