Triple
T25741180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OS Explorer OL57 |
E648220
|
entity |
| Predicate | hasTopographicDetailLevel |
P165004
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [OS Explorer OL57, hasTopographicDetailLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTopographicDetailLevel Context triple: [OS Explorer OL57, hasTopographicDetailLevel, high]
-
A.
hasTopographicContext
Indicates that one entity is related to or characterized by a particular topographic or physical landscape context.
-
B.
hasElevationData
Indicates that an entity is associated with specific elevation or height information, such as altitude values or elevation measurements.
-
C.
hasTopographicEffect
Indicates that one entity causes or contributes to a change or influence on the physical terrain or topography of another entity or area.
-
D.
topographicMap
Indicates a mapping relationship where a representation shows the physical terrain features and elevation contours of a geographic area.
-
E.
hasTopElevation
Indicates that an entity has a specified maximum or highest elevation value.
- F. None of above. chosen
Provenance (4 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 22, 2026, 3:43 a.m.