Triple
T24229221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordaustlandet |
E601680
|
entity |
| Predicate | rankByAreaInSvalbard |
P143409
|
FINISHED |
| Object | second-largest island |
—
|
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 island | Statement: [Nordaustlandet, rankByAreaInSvalbard, second-largest island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInSvalbard Context triple: [Nordaustlandet, rankByAreaInSvalbard, second-largest island]
-
A.
rankInNorwayByArea
Indicates the position of an entity in an ordered list of areas within Norway, based on its size relative to others.
-
B.
rankByAreaInCanadaIslands
Indicates the numerical position of an island in Canada when all Canadian islands are ordered by their land area from largest to smallest.
-
C.
rankInArchipelagoByArea
chosen
Indicates the position of an island in a size-based ordering of islands within the same archipelago, based on their land area.
-
D.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
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.
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_69e29538aafc8190a2386fdebbd1393b |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f287e214e88190bf6d5b0f5f489f73 |
completed | April 29, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:01 a.m.