Triple
T83367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester City F.C. |
E1675
|
entity |
| Predicate | homeCapacity |
P2491
|
FINISHED |
| Object | Etihad Stadium seating over 50,000 spectators |
—
|
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: Etihad Stadium seating over 50,000 spectators | Statement: [Manchester City F.C., homeCapacity, Etihad Stadium seating over 50,000 spectators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCapacity Context triple: [Manchester City F.C., homeCapacity, Etihad Stadium seating over 50,000 spectators]
-
A.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
B.
seatingCapacity
chosen
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
C.
house
Indicates that one entity serves as a dwelling or residence for another entity.
-
D.
houses
Indicates that one entity serves as a dwelling or shelter for another entity.
-
E.
floorCount
Indicates the number of floors or levels that a building or structure has.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f4ccb5081908decac81f4af01bf |
completed | Feb. 28, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69a24eb469548190b38c24e81f36c838 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.