Triple
T9080425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silhouette Island |
E217604
|
entity |
| Predicate | hasHumanSettlementLevel |
P70399
|
FINISHED |
| Object | low |
—
|
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: low | Statement: [Silhouette Island, hasHumanSettlementLevel, low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumanSettlementLevel Context triple: [Silhouette Island, hasHumanSettlementLevel, low]
-
A.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
B.
humanSettlementLevel
chosen
Indicates the degree or intensity of human settlement present in a given area, such as how densely or extensively it is inhabited or developed.
-
C.
hasCityStatusSettlement
Indicates that a settlement possesses official recognition or designation as a city.
-
D.
hasMunicipalLevel
Indicates that an entity is associated with a specific level or tier within a municipal (local government) hierarchy.
-
E.
humanSettlementStatus
Indicates the classification of a place in terms of its status as a human settlement (e.g., whether and how it is recognized or designated as a populated place).
- 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9607942c8190a21620892ce3cbe5 |
completed | April 1, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:13 p.m.