Triple
T36255596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brighton Mile Challenge Trophy Handicap |
E891926
|
entity |
| Predicate | hasUnitOfLength |
P145577
|
FINISHED |
| Object | mile |
—
|
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: mile | Statement: [Brighton Mile Challenge Trophy Handicap, hasUnitOfLength, mile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnitOfLength Context triple: [Brighton Mile Challenge Trophy Handicap, hasUnitOfLength, mile]
-
A.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
B.
hasSystemLengthUnit
Indicates that a system or context uses a specified unit of length as its standard measurement unit.
-
C.
hasUnitIn
Indicates that one entity is contained or measured within another as a unit, specifying a unit-of-measure or component relationship.
-
D.
hasDistanceUnit
chosen
Indicates that a specified unit of measurement is used to express a distance value in the relationship.
-
E.
isAUnitOf
Indicates that one entity functions as a unit or standard measure in which the other entity is quantified or expressed.
- 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_69f76e4599108190811532e707d6bc2c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: May 3, 2026, 4:09 p.m.