Triple
T23509338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Chair |
E572372
|
entity |
| Predicate | fenceNumber |
P151152
|
FINISHED |
| Object | 15th fence in the Grand National |
—
|
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: 15th fence in the Grand National | Statement: [The Chair, fenceNumber, 15th fence in the Grand National]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fenceNumber Context triple: [The Chair, fenceNumber, 15th fence in the Grand National]
-
A.
appearsAsFenceNumber
chosen
Indicates that an entity is used or shown as a specific fence identification number in a given context.
-
B.
numberOfFences
Indicates the quantity of fences associated with or present around a given entity.
-
C.
yardNumber
Indicates the identifying number assigned to a specific yard or yard-related unit within a larger system or location.
-
D.
hasGateNumber
Indicates that an entity (such as a flight or departure) is associated with a specific gate number.
-
E.
fences
Indicates that one entity constructs, installs, or maintains a fence or barrier around or between entities or areas.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a902c0788190840d7df1b5450b4d |
completed | April 29, 2026, 6:45 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:07 p.m.