Triple
T32380872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Island of Ireland |
E827411
|
entity |
| Predicate | rankByAreaInEurope |
P17043
|
FINISHED |
| Object | third-largest island in Europe |
—
|
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: third-largest island in Europe | Statement: [Island of Ireland, rankByAreaInEurope, third-largest island in Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInEurope Context triple: [Island of Ireland, rankByAreaInEurope, third-largest island in Europe]
-
A.
areaRankingInEurope
chosen
Indicates the position of an entity in a size-based ranking of areas within Europe.
-
B.
rankByLengthInEurope
Indicates that entities are ordered or compared based on their length specifically within the context of Europe.
-
C.
rankingInEurope
Indicates the position or level an entity holds within a comparative ranking limited to Europe.
-
D.
rankInGermanyByArea
Indicates the position of an entity in an ordered list based on its area size within Germany.
-
E.
rankInFinlandByArea
Indicates the position of an entity in an ordered list based on its area size within Finland.
- 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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:51 a.m.