Triple
T19422315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beinn a’ Chaolais |
E485885
|
entity |
| Predicate | relativeHeightRankOnJura |
P135820
|
FINISHED |
| Object | one of the highest peaks on Jura |
—
|
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: one of the highest peaks on Jura | Statement: [Beinn a’ Chaolais, relativeHeightRankOnJura, one of the highest peaks on Jura]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeHeightRankOnJura Context triple: [Beinn a’ Chaolais, relativeHeightRankOnJura, one of the highest peaks on Jura]
-
A.
heightRankingInSwitzerland
Indicates the relative position of an entity in an ordered list based on its height specifically within the context of Switzerland.
-
B.
regionRankByHeight
Indicates the relative ordering of regions based on their height or elevation.
-
C.
rankByHeightInAustria
Indicates that entities are ordered or compared according to their height specifically within the context of Austria.
-
D.
relativeHeightRankInWales
Indicates the position of something in an ordered ranking based on its height relative to all comparable entities located in Wales.
-
E.
rankingByHeightInJapan
Indicates the relative order of entities based on their height specifically within the context of Japan.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e632159d7081909d004544ec5992c0 |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:37 p.m.