Triple
T33648044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunslet Engine Company |
E862014
|
entity |
| Predicate | railGaugeSpecialism |
P5070
|
FINISHED |
| Object | narrow gauge |
—
|
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: narrow gauge | Statement: [Hunslet Engine Company, railGaugeSpecialism, narrow gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railGaugeSpecialism Context triple: [Hunslet Engine Company, railGaugeSpecialism, narrow gauge]
-
A.
railwayGaugeContext
Indicates the specific track gauge standard or measurement that applies to, or is used in, a given railway-related context.
-
B.
usesRailGauge
chosen
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
C.
railcode
Indicates that an entity is associated with a specific railway code used for identification or classification within a rail system.
-
D.
railStandard
Indicates that something conforms to, uses, or is governed by a particular railway or rail transport standard.
-
E.
railwayFocus
Indicates that something is a primary subject, theme, or point of attention specifically in the context of railways or railway-related matters.
- 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:42 a.m.