Triple
T12902719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Face of Annapurna |
E308649
|
entity |
| Predicate | verticalRelief |
P10733
|
FINISHED |
| Object | approximately 3000 metres |
—
|
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: approximately 3000 metres | Statement: [South Face of Annapurna, verticalRelief, approximately 3000 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: verticalRelief Context triple: [South Face of Annapurna, verticalRelief, approximately 3000 metres]
-
A.
verticalLocation
Indicates a vertical positional relationship where one entity is located above or below another along the up-down axis.
-
B.
hasRelativeRelief
Indicates a relationship where one entity is characterized by the degree of variation in elevation or relief relative to another reference entity or area.
-
C.
verticalExtent
chosen
Indicates the total height or vertical span of an entity or region from its lowest to highest point.
-
D.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
E.
verticalOrder
Indicates that one entity is positioned directly above or below another along a vertical axis, establishing their relative vertical arrangement.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971820e008190bf8bc7c392c8bcbb |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:40 p.m.