Triple
T7056437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praslin |
E164103
|
entity |
| Predicate | rankByAreaInSeychelles |
P74778
|
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: [Praslin, rankByAreaInSeychelles, second-largest island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInSeychelles Context triple: [Praslin, rankByAreaInSeychelles, second-largest island]
-
A.
rankByAreaInCanadaIslands
Indicates the numerical position of an island in Canada when all Canadian islands are ordered by their land area from largest to smallest.
-
B.
rankByAreaInCaribbean
Indicates the relative ordering of entities based on their area size specifically within the Caribbean region.
-
C.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
D.
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.
-
E.
areaRankingInTurksAndCaicos
Indicates the relative position of an entity in a size-based ranking specifically within the Turks and Caicos Islands.
- 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_69c68861678881909961ddf4d779f750 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e4a15b088190bee9a23e94aaac53 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:38 p.m.