Triple
T2485072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abruzzi Spur |
E55905
|
entity |
| Predicate | typicalCamp1Altitude_m |
P40319
|
FINISHED |
| Object | 6000 |
—
|
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: 6000 | Statement: [Abruzzi Spur, typicalCamp1Altitude_m, 6000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCamp1Altitude_m Context triple: [Abruzzi Spur, typicalCamp1Altitude_m, 6000]
-
A.
typicalElevationRange
Indicates the usual range of elevation values within which something commonly occurs or exists.
-
B.
typicalAscentStartPoint
Indicates the usual or most common location from which an ascent or climb is begun.
-
C.
hasAverageElevation
Indicates that an entity is characterized by a specific mean height above a defined reference level, typically sea level.
-
D.
higherCamp
Indicates that one camp is located at a higher elevation or position relative to another camp.
-
E.
altitudeCategory
Indicates the classification of something based on its height or elevation relative to a reference level (e.g., low, medium, high altitude).
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.