Triple
T37531999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langjökull |
E933075
|
entity |
| Predicate | rankByAreaInIceland |
P188209
|
FINISHED |
| Object | second-largest ice cap in Iceland |
—
|
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-largest ice cap in Iceland | Statement: [Langjökull, rankByAreaInIceland, second-largest ice cap in Iceland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInIceland Context triple: [Langjökull, rankByAreaInIceland, second-largest ice cap in Iceland]
-
A.
rankInSwedenByArea
Indicates the position of an entity in an ordered list based on its area size within Sweden.
-
B.
rankInFinlandByArea
Indicates the position of an entity in an ordered list based on its area size within Finland.
-
C.
rankInNorwayByArea
Indicates the position of an entity in an ordered list of areas within Norway, based on its size relative to others.
-
D.
distanceFromReykjavík
Indicates the spatial distance between an entity’s location and the city of Reykjavík.
-
E.
rankInBritishIslesByArea
Indicates the position of an entity in an ordered list of areas specifically within the British Isles, based on its size relative to others.
- 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_69f76ec8862c8190bfa24145f5480642 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba5ee00fc81909be7b947a3f95034 |
completed | May 6, 2026, 8:34 p.m. |
Created at: May 3, 2026, 4:17 p.m.