Triple
T22304316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodyear Ballpark |
E551334
|
entity |
| Predicate | distanceFromDowntownPhoenixApproxMiles |
P1299
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Goodyear Ballpark, distanceFromDowntownPhoenixApproxMiles, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDowntownPhoenixApproxMiles Context triple: [Goodyear Ballpark, distanceFromDowntownPhoenixApproxMiles, 20]
-
A.
distanceToPhoenix
Indicates the measured or estimated distance between a given entity’s location and the city of Phoenix.
-
B.
distanceFromTucson
Indicates the spatial distance between a given entity and the location of Tucson.
-
C.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
D.
distanceToSedona
Indicates the measured or calculated spatial distance between a given entity’s location and the location of Sedona.
-
E.
distanceFromLasVegas
Indicates the measured distance between a given place or object and the city of Las Vegas.
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15725de488190a32006cd99dd4a67 |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e72ffa438481908f80879aef2a589b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:41 p.m.