Triple
T25314945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Class 317 |
E634708
|
entity |
| Predicate | totalLengthPerUnit |
P140284
|
FINISHED |
| Object | approximately 80 metres |
—
|
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: approximately 80 metres | Statement: [British Rail Class 317, totalLengthPerUnit, approximately 80 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalLengthPerUnit Context triple: [British Rail Class 317, totalLengthPerUnit, approximately 80 metres]
-
A.
totalLength_m
chosen
Indicates the overall measured length of something expressed in meters.
-
B.
circuitLengthUnit
Indicates the unit of measurement used to express the length of a circuit.
-
C.
commonTotalLength
Indicates that the entities share the same overall measured length.
-
D.
dimensionOfLength
Indicates that something represents or specifies a measurement along a single spatial extent (a length dimension).
-
E.
numberOfUnits
Indicates the quantity or count of discrete units associated with an entity or relationship.
- 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_69e75a9847c08190bb02990d06d5ffb7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 1:27 p.m.