Triple
T24814068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Class 745 |
E620866
|
entity |
| Predicate | totalUnits |
P19248
|
FINISHED |
| Object | 20 units |
—
|
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: 20 units | Statement: [British Rail Class 745, totalUnits, 20 units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalUnits Context triple: [British Rail Class 745, totalUnits, 20 units]
-
A.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
B.
someUnitsConvertedTo
Indicates that a quantity expressed in one unit of measurement has been transformed into an equivalent quantity expressed in another unit.
-
C.
multipleUnit
Indicates that an entity is composed of or associated with more than one unit of the same type.
-
D.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
E.
numberOfUnitsCommanded
Indicates the quantity of units that an entity is in command of within 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:59 a.m.