Triple
T23296403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Málaga María Zambrano railway station |
E590181
|
entity |
| Predicate | hasHighSpeedTracks |
P145129
|
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: [Málaga María Zambrano railway station, hasHighSpeedTracks, standard gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighSpeedTracks Context triple: [Málaga María Zambrano railway station, hasHighSpeedTracks, standard gauge]
-
A.
hasHighSpeedLine
Indicates that there exists a high-speed rail line connection between the related entities.
-
B.
hasHighSpeedSections
chosen
Indicates that the entity includes segments or portions where operation or movement occurs at high speed.
-
C.
hasUndergroundHighSpeedPlatforms
Indicates that an entity is equipped with high-speed transportation platforms located underground.
-
D.
hasExpressTracks
Indicates that a transportation route or facility includes tracks designated for express service, allowing faster travel with fewer stops than regular tracks.
-
E.
hasHighSpeedRailStation
Indicates that a location is served by a high-speed rail station where high-speed trains regularly stop.
- 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_69e25d1af9d88190a0b9b5e8fa608618 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196cfc79081909966638cec48cf60 |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:03 p.m.