Triple
T30953037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid–Zaragoza–Lleida high-speed line |
E788597
|
entity |
| Predicate | trackGaugeValue |
P391
|
FINISHED |
| Object | 1435 mm |
—
|
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: 1435 mm | Statement: [Madrid–Zaragoza–Lleida high-speed line, trackGaugeValue, 1435 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackGaugeValue Context triple: [Madrid–Zaragoza–Lleida high-speed line, trackGaugeValue, 1435 mm]
-
A.
trackGauge
chosen
Indicates the distance between the inner faces of the rails in a railway track system.
-
B.
trackGaugeUnit
Indicates the unit of measurement used to express the gauge (width) of a track.
-
C.
trackGaugeOptions
Indicates the available or applicable gauge (measurement) configurations that can be used for a given track.
-
D.
formerTrackGauge
Indicates that an entity previously had a specified track gauge, which has since been changed or is no longer in use.
-
E.
gaugeValue
Indicates the measured or current reading associated with a particular gauge or measurement instrument.
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 29, 2026, 8:53 p.m.