Triple
T2956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Campanas Observatory |
E55
|
entity |
| Predicate | altitude |
P221
|
FINISHED |
| Object | approximately 2400 meters |
—
|
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 2400 meters | Statement: [Las Campanas Observatory, altitude, approximately 2400 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: altitude Context triple: [Las Campanas Observatory, altitude, approximately 2400 meters]
-
A.
elevation
chosen
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
B.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
C.
lowestPoint
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified context.
-
D.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
- 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_69a2328f0e848190ac2840eaf2d5ebd2 |
completed | Feb. 28, 2026, 12:10 a.m. |
| NER | Named-entity recognition | batch_69a2346846608190b6b40d31f1dbd685 |
completed | Feb. 28, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69a233c396ec8190986608d07fb251d4 |
completed | Feb. 28, 2026, 12:16 a.m. |
Created at: Feb. 28, 2026, 12:13 a.m.