Triple
T4386456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belmont Stakes |
E99253
|
entity |
| Predicate | usualDistanceSince |
P2935
|
FINISHED |
| Object | 1.5 miles since 1926 |
—
|
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: 1.5 miles since 1926 | Statement: [Belmont Stakes, usualDistanceSince, 1.5 miles since 1926]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usualDistanceSince Context triple: [Belmont Stakes, usualDistanceSince, 1.5 miles since 1926]
-
A.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
B.
usedSince
chosen
Indicates that an entity has been in use starting from a specified point in time and continuing thereafter.
-
C.
usuallyFrom
Indicates that something typically originates, is derived, or comes from a particular source or location.
-
D.
distanceStandard
Indicates that a specified distance between entities is measured or evaluated according to a particular standard or reference criterion.
-
E.
near
Indicates that one entity is located at a short distance from another entity in space or position.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352669f608190b3aa7030d8073e04 |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:19 p.m.