Triple
T16470944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LMS Ivatt Class 2 2-6-0 |
E400056
|
entity |
| Predicate | BRBuiltQuantity |
P2091
|
FINISHED |
| Object | 108 |
—
|
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: 108 | Statement: [LMS Ivatt Class 2 2-6-0, BRBuiltQuantity, 108]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BRBuiltQuantity Context triple: [LMS Ivatt Class 2 2-6-0, BRBuiltQuantity, 108]
-
A.
numberBuilt
chosen
Indicates the total count of items or structures that have been constructed or produced.
-
B.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
C.
buildingInvolved
Indicates that a particular building participates in, is affected by, or is otherwise relevant to the specified event or relationship.
-
D.
builtProperty
Indicates that a constructed structure or building has been created on, or is associated with, a particular property or piece of land.
-
E.
buildingNumber
Indicates the specific numeric identifier assigned to a building within an address or location.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dd0d2fc81909b68b5afb00f192f |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:11 a.m.