Triple
T1469410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Water Island |
E27099
|
entity |
| Predicate | mainSettlementType |
P14278
|
FINISHED |
| Object | scattered residential communities |
—
|
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: scattered residential communities | Statement: [Water Island, mainSettlementType, scattered residential communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainSettlementType Context triple: [Water Island, mainSettlementType, scattered residential communities]
-
A.
mainSettlement
Indicates that one settlement serves as the primary or most important settlement associated with a given area, region, or administrative unit.
-
B.
humanSettlementType
chosen
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
C.
hasCityStatusSettlement
Indicates that a settlement possesses official recognition or designation as a city.
-
D.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
E.
originalSettlement
Indicates that one entity is the initial or first-established settlement location associated with another entity.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5d8bb68819095b7b413247ad657 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.