Triple
T5626679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gran Vía metro station |
E147732
|
entity |
| Predicate | hasZoneClassification |
P36294
|
FINISHED |
| Object | central zone |
—
|
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: central zone | Statement: [Gran Vía metro station, hasZoneClassification, central zone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasZoneClassification Context triple: [Gran Vía metro station, hasZoneClassification, central zone]
-
A.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
B.
hasRegionDesignation
Indicates that an entity is assigned or associated with a specific regional classification or designation.
-
C.
zoneType
chosen
Indicates the classification or category of a zone that specifies its type or functional designation.
-
D.
supportsZoneSystem
Indicates that one entity provides compatibility with or implementation of a specific zone-based system used by another entity.
-
E.
hasRailwayZone
Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
- 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_69c00906f2a88190a992c66b13d606d4 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02237dd6081909f6a7d710b9cd651 |
completed | March 22, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69c01b1d4b108190846ce586dc783acf |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:40 p.m.