Triple
T34467976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Coll | La Teixonera |
E884825
|
entity |
| Predicate | servesTopography |
P87992
|
FINISHED |
| Object | hilly area |
—
|
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: hilly area | Statement: [El Coll | La Teixonera, servesTopography, hilly area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesTopography Context triple: [El Coll | La Teixonera, servesTopography, hilly area]
-
A.
topographyBasedOn
Indicates that the topographical characteristics of one entity are derived from, determined by, or modeled using the topography of another entity.
-
B.
associatedTopography
chosen
Indicates a relationship where one entity is linked or connected to a particular topographical feature or terrain.
-
C.
hasTopographicContext
Indicates that one entity is related to or characterized by a particular topographic or physical landscape context.
-
D.
topographicListing
Indicates a relationship where one entity is included as an entry within a topographic or terrain-related listing or catalog of another entity.
-
E.
hasTopographicEffect
Indicates that one entity causes or contributes to a change or influence on the physical terrain or topography of another entity or 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_69f349c880408190ade571c471ab154a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffb1f0b03c81909ddb81f07ce74e88 |
completed | May 9, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ffb1662b2481908582e0612744f4c5 |
completed | May 9, 2026, 10:12 p.m. |
Created at: May 1, 2026, 2:01 a.m.