Triple
T17787787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokara Islands |
E444064
|
entity |
| Predicate | hasUninhabitedIslands |
P128924
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Tokara Islands, hasUninhabitedIslands, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUninhabitedIslands Context triple: [Tokara Islands, hasUninhabitedIslands, 5]
-
A.
hasNumberOfInhabitedIslands
Indicates the relationship that specifies how many islands within a given area or jurisdiction are inhabited.
-
B.
hasNotableIslandGroup
Indicates that a place or region includes or is associated with a particularly significant or well-known group of islands.
-
C.
hasIslandNation
Indicates that one entity is an island-based sovereign state associated with or possessed by another entity.
-
D.
hasMajorIslandToSouth
Indicates that the subject entity has a major island located geographically to its south.
-
E.
hasNumberOfMajorIslands
Indicates the quantitative relationship specifying how many major islands are associated with a given 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48794542c8190b049bce6e28c9f3a |
completed | April 19, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:12 a.m.