Triple
T24501495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OS Landranger 90 |
E617943
|
entity |
| Predicate | includesTopographicDetail |
P10300
|
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: [OS Landranger 90, includesTopographicDetail, contour lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesTopographicDetail Context triple: [OS Landranger 90, includesTopographicDetail, contour lines]
-
A.
hasTopographicContext
Indicates that one entity is related to or characterized by a particular topographic or physical landscape context.
-
B.
topographicMap
chosen
Indicates a mapping relationship where a representation shows the physical terrain features and elevation contours of a geographic area.
-
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.
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.
topographyBasedOn
Indicates that the topographical characteristics of one entity are derived from, determined by, or modeled using the topography of 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_69e2d7f682108190a1a7ca5fd485ee8a |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:23 a.m.