Triple
T7982956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spotify Camp Nou |
E185617
|
entity |
| Predicate | capacityRanking |
P31373
|
FINISHED |
| Object | largest football stadium in Europe by capacity |
—
|
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: largest football stadium in Europe by capacity | Statement: [Spotify Camp Nou, capacityRanking, largest football stadium in Europe by capacity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityRanking Context triple: [Spotify Camp Nou, capacityRanking, largest football stadium in Europe by capacity]
-
A.
capacityRank
chosen
Indicates the relative ordering of entities based on how much capacity (e.g., volume, throughput, or capability) they possess compared to others.
-
B.
rankingScope
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
C.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
D.
rankingType
Indicates the specific basis or method by which items are ordered or ranked relative to one another.
-
E.
rankingCategory
Indicates the classification or type of ranking under which an entity is evaluated or ordered.
- 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c2a1aa881909c3cea280dff38f5 |
completed | March 31, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69cb048009a08190b4c577208a9f8f76 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:15 p.m.