Triple
T551893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geneva–Lyon railway |
E11857
|
entity |
| Predicate | usesGauge |
P5070
|
FINISHED |
| Object | standard 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: standard gauge | Statement: [Geneva–Lyon railway, usesGauge, standard gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesGauge Context triple: [Geneva–Lyon railway, usesGauge, standard gauge]
-
A.
gaugeGroup
Indicates a relationship where a physical or theoretical model is associated with the gauge group that defines its underlying symmetry structure.
-
B.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
-
C.
hasMeter
Indicates that one entity possesses, uses, or is associated with a specific meter (a measuring device or metrical pattern).
-
D.
usesRailGauge
chosen
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
E.
usesMetric
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499047bd4819089ca8345f1b6e46c |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.