Triple
T618946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vuelta a España |
E14467
|
entity |
| Predicate | terrainCharacteristics |
P9701
|
FINISHED |
| Object | mountainous |
—
|
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: mountainous | Statement: [Vuelta a España, terrainCharacteristics, mountainous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrainCharacteristics Context triple: [Vuelta a España, terrainCharacteristics, mountainous]
-
A.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
B.
landscapeType
chosen
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
C.
hasGeographyCharacteristic
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
D.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
E.
topographicMap
Indicates a mapping relationship where a representation shows the physical terrain features and elevation contours of a geographic area.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e25956c8190a1eed87002548658 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfd15288190b4abdbd0bce3edcd |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.