Triple
T22308771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Class 153 |
E551456
|
entity |
| Predicate | conversionYears |
P75841
|
FINISHED |
| Object | 1991–1992 |
—
|
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: 1991–1992 | Statement: [British Rail Class 153, conversionYears, 1991–1992]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conversionYears Context triple: [British Rail Class 153, conversionYears, 1991–1992]
-
A.
countsYearsFrom
Indicates a temporal relationship where the number of years is measured starting from a specified reference point or event.
-
B.
type2Years
Indicates the number of years associated with a type 2 classification, status, or condition in the given context.
-
C.
durationInYears
chosen
Indicates the length of time associated with something, measured in whole or fractional years.
-
D.
approximateTimeInYear
Indicates that one time-related entity represents an estimated or non-exact point or interval within a given year for another entity.
-
E.
yearPassed
Indicates that a specified number of calendar years has elapsed between two time points or events.
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1574c8a248190bf5eef5be78381fd |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e72ffa438481908f80879aef2a589b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.