Triple
T8599847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clew Bay |
E203645
|
entity |
| Predicate | hasApproximateIslandsCount |
P83793
|
FINISHED |
| Object | hundreds of islands and islets |
—
|
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: hundreds of islands and islets | Statement: [Clew Bay, hasApproximateIslandsCount, hundreds of islands and islets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateIslandsCount Context triple: [Clew Bay, hasApproximateIslandsCount, hundreds of islands and islets]
-
A.
hasNumberOfMajorIslands
Indicates the quantitative relationship specifying how many major islands are associated with a given entity.
-
B.
hasNumberOfInhabitedIslands
Indicates the relationship that specifies how many islands within a given area or jurisdiction are inhabited.
-
C.
hasIslandAreaApprox
Indicates that an island’s area is approximately equal to a specified value or falls within an approximate range.
-
D.
numberOfConstituentIslands
Indicates the count of individual islands that collectively make up a larger island group or entity.
-
E.
numberOfIslandsAndReefs
Indicates the count of islands and reefs associated with or contained within a given geographic or administrative entity.
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46d7c184819083236c75f9ccc9cf |
completed | March 31, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cc454eb2908190acf0e4336bc67e7b |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:24 p.m.