Triple
T19402847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Major |
E485370
|
entity |
| Predicate | hasMapCoverage |
P1987
|
FINISHED |
| Object | USGS topographic maps |
—
|
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: USGS topographic maps | Statement: [Mount Major, hasMapCoverage, USGS topographic maps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMapCoverage Context triple: [Mount Major, hasMapCoverage, USGS topographic maps]
-
A.
mapCoverage
chosen
Indicates the extent or area that is represented, covered, or included by a particular map.
-
B.
hasMapRegion
Indicates that an entity is associated with, or belongs to, a specific geographic or logical map region.
-
C.
hasMapframe
Indicates that an entity is associated with an embedded, interactive map frame representation of its geographic location or area.
-
D.
hasCoverFeature
Indicates that one entity serves as a prominent or featured element on the cover of another entity (such as a publication, product, or media item).
-
E.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62577f808819099e74feab82b34a4 |
completed | April 20, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:36 p.m.