Triple
T749409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polo Grounds |
E15412
|
entity |
| Predicate | capacityPeak |
P14460
|
FINISHED |
| Object | over 50,000 |
—
|
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: over 50,000 | Statement: [Polo Grounds, capacityPeak, over 50,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityPeak Context triple: [Polo Grounds, capacityPeak, over 50,000]
-
A.
annualCapacity
Indicates the maximum amount of output or throughput an entity can produce or handle within a one-year period.
-
B.
maximumCapacity
chosen
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
C.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
D.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
E.
maxCurrent
Indicates the maximum electric current that is allowed to flow through or be drawn by an entity under specified conditions.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a6304e0c8190827fb57c5cac2da9 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a5004f708190a984ee221716e19c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.