Triple
T23296404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Málaga María Zambrano railway station |
E590181
|
entity |
| Predicate | hasConventionalTracks |
P115884
|
FINISHED |
| Object | Iberian 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: Iberian gauge | Statement: [Málaga María Zambrano railway station, hasConventionalTracks, Iberian gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConventionalTracks Context triple: [Málaga María Zambrano railway station, hasConventionalTracks, Iberian gauge]
-
A.
hasTwoTracks
Indicates that the subject possesses or is associated with exactly two distinct tracks or pathways.
-
B.
hasTrackFeatures
chosen
Indicates that something possesses or is associated with specific track-related characteristics or attributes.
-
C.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
D.
containsAdditionalTracksBeyond
Indicates that one entity includes more tracks or items than are present in another referenced set or version.
-
E.
standardEditionTracks
Indicates that the related tracks are those included in the standard (non-deluxe) edition of a release.
- 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.