Triple
T26301926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mapa Topográfico Nacional de España |
E661580
|
entity |
| Predicate | featureShown |
P41649
|
FINISHED |
| Object | contour lines |
—
|
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: contour lines | Statement: [Mapa Topográfico Nacional de España, featureShown, contour lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureShown Context triple: [Mapa Topográfico Nacional de España, featureShown, contour lines]
-
A.
displaysFeature
chosen
Indicates that one entity presents, shows, or makes visible a particular feature or characteristic of another entity.
-
B.
featuresMode
Indicates that one entity operates in, supports, or is characterized by a particular mode or configuration specified by another entity.
-
C.
featuresDemon
Indicates that an entity includes, depicts, or prominently involves a demon.
-
D.
featuresSetting
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
E.
featuresPreShow
Indicates that one entity includes or presents a pre-show segment or content associated with another entity.
- 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_69ee812cd48c81908054068f545f0526 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: April 26, 2026, 10:16 p.m.