Triple
T2303013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camp Nou |
E51773
|
entity |
| Predicate | capacityRankInWorld |
P38632
|
FINISHED |
| Object | among largest football stadiums |
—
|
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: among largest football stadiums | Statement: [Camp Nou, capacityRankInWorld, among largest football stadiums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityRankInWorld Context triple: [Camp Nou, capacityRankInWorld, among largest football stadiums]
-
A.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
B.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
countryRanking
Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
-
D.
hasPopulationRankInRegion
Indicates that an entity has a specific population-based rank or position within a defined geographic region.
-
E.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
- F. None of above. chosen
Provenance (4 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcbabf01081908db3b42bc7c60444 |
completed | March 7, 2026, 6:54 a.m. |
| PD | Predicate disambiguation | batch_69abc58ad33c8190b8d68af41b6f5e07 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcbab15488190bc8d2345f9d9f2bd |
completed | March 7, 2026, 6:54 a.m. |
Created at: March 4, 2026, 7:49 p.m.