Triple
T13077090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smoking Mountain |
E329605
|
entity |
| Predicate | rankByElevationInMexico |
P39147
|
FINISHED |
| Object | second highest mountain in Mexico |
—
|
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 Mexico | Statement: [Smoking Mountain, rankByElevationInMexico, second highest mountain in Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByElevationInMexico Context triple: [Smoking Mountain, rankByElevationInMexico, second highest mountain in Mexico]
-
A.
rankInNorthAmericaByElevation
Indicates the relative position of a place in an ordered list of locations in North America based on their elevation.
-
B.
populationRankInMexico
Indicates the relative position of an entity in terms of population size compared to other entities within Mexico.
-
C.
summitElevationRank
chosen
Indicates the relative position of a summit in an ordered list based on its elevation compared to other summits.
-
D.
countryHighestPointRank
Indicates the relative ranking of a country's highest natural elevation compared to the highest points of other countries.
-
E.
regionRankByHeight
Indicates the relative ordering of regions based on their height or elevation.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9811828448190ac6ddd3e9c221251 |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:01 p.m.