Triple
T722605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glentoran FC |
E14650
|
entity |
| Predicate | groundCapacity |
P13466
|
FINISHED |
| Object | The Oval capacity about 15,000 |
—
|
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: The Oval capacity about 15,000 | Statement: [Glentoran FC, groundCapacity, The Oval capacity about 15,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: groundCapacity Context triple: [Glentoran FC, groundCapacity, The Oval capacity about 15,000]
-
A.
ground
Indicates that one entity is in contact with or supported by the ground or a ground-like surface.
-
B.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
C.
annualCapacity
Indicates the maximum amount of output or throughput an entity can produce or handle within a one-year period.
-
D.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
E.
totalCapacity
chosen
Indicates the maximum amount or volume that something can hold or accommodate in total.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a591124c8190842e7ef18b064198 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f700cc81908c6de3eedf68433c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.