Triple
T10742350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nou Camp |
E253357
|
entity |
| Predicate | averageAnnualVisitors |
P12597
|
FINISHED |
| Object | over 3 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: over 3 million | Statement: [Nou Camp, averageAnnualVisitors, over 3 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageAnnualVisitors Context triple: [Nou Camp, averageAnnualVisitors, over 3 million]
-
A.
typicalVisitorsPerSeason
Indicates the usual number of visitors associated with each season for a given entity or location.
-
B.
touristArrivalsPerYearApprox
chosen
Indicates an approximate count of how many tourists arrive at a place over the course of a year.
-
C.
touristArrivalsShareInTerritory
Indicates the proportion of total tourist arrivals that occur within a specific territory relative to a larger reference area or total.
-
D.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
E.
annualVisitation
Indicates a recurring visit or attendance that takes place once every year between the related entities.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710456ec88190ad8aff8804d13aa9 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:15 p.m.