Triple
T11399112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Karakoram expedition of 1954 |
E270059
|
entity |
| Predicate | peakRankByHeight |
P2472
|
FINISHED |
| Object | second-highest mountain in the world |
—
|
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: second-highest mountain in the world | Statement: [Italian Karakoram expedition of 1954, peakRankByHeight, second-highest mountain in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakRankByHeight Context triple: [Italian Karakoram expedition of 1954, peakRankByHeight, second-highest mountain in the world]
-
A.
regionRankByHeight
Indicates the relative ordering of regions based on their height or elevation.
-
B.
peakRanking
Indicates the highest position or rank an entity has ever achieved within a specified ranking system or context.
-
C.
peakRating
Indicates the highest rating value that has been achieved or recorded for an entity over a given period or context.
-
D.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
E.
rankByHeightWorld
chosen
Indicates an ordering of entities based on their relative height compared to all others in the world.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001adc188190ae45227856156412 |
completed | April 9, 2026, 7:38 p.m. |
| PD | Predicate disambiguation | batch_69d7e70b228c8190b87f5101fd683788 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.