Triple
T509429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yankee Stadium |
E10572
|
entity |
| Predicate | builtAcrossStreetFrom |
P14545
|
FINISHED |
| Object | original Yankee Stadium site |
—
|
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: original Yankee Stadium site | Statement: [Yankee Stadium, builtAcrossStreetFrom, original Yankee Stadium site]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: builtAcrossStreetFrom Context triple: [Yankee Stadium, builtAcrossStreetFrom, original Yankee Stadium site]
-
A.
crossedBy
Indicates that one entity (typically a path, line, or boundary) is intersected or traversed by another entity.
-
B.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
C.
crossedByRiver
Indicates that a river passes across or through a specified area, feature, or route.
-
D.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
-
E.
locatedAcrossRiverFrom
Indicates that one entity is situated on the opposite side of a river relative to another entity.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f164a9d48190b525a97b5c06ffe2 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edfe236481909901cc7d4281b33c |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.