Triple
T1058570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michipicoten Island |
E22852
|
entity |
| Predicate | humanSettlement |
P16159
|
FINISHED |
| Object | no permanent town |
—
|
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: no permanent town | Statement: [Michipicoten Island, humanSettlement, no permanent town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: humanSettlement Context triple: [Michipicoten Island, humanSettlement, no permanent town]
-
A.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
B.
humanSettlementInside
Indicates that one human settlement is located entirely within the geographic boundaries of another area or settlement.
-
C.
mainSettlement
Indicates that one settlement serves as the primary or most important settlement associated with a given area, region, or administrative unit.
-
D.
traditionalSettlement
Indicates that an entity is a settlement characterized by long-established, customary, or historically rooted patterns of habitation and land use.
-
E.
hasHumanSettlement
chosen
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4ba6e35ac8190802341c31bda0e3b |
completed | March 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69a4b7340a048190807363f19d17a58f |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.