Triple
T17791096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sussex Stakes |
E444162
|
entity |
| Predicate | originalDistance |
P128748
|
FINISHED |
| Object | 6 furlongs |
—
|
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: 6 furlongs | Statement: [Sussex Stakes, originalDistance, 6 furlongs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalDistance Context triple: [Sussex Stakes, originalDistance, 6 furlongs]
-
A.
formerDistance
chosen
Indicates that a distance or spatial separation between entities existed in the past but no longer holds in the present.
-
B.
primaryDistance
Indicates the main or most significant measure of distance between two entities in the relationship.
-
C.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another entity.
-
D.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
E.
numberOfDistances
Indicates the count of distinct distance values associated with or measured between entities in a given context.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48797408081908c48d98e1525ae87 |
completed | April 19, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:13 a.m.