Triple
T23341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha's Vineyard |
E463
|
entity |
| Predicate | hasLandArea |
P157
|
FINISHED |
| Object | approximately 260 square kilometers |
—
|
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: approximately 260 square kilometers | Statement: [Martha's Vineyard, hasLandArea, approximately 260 square kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandArea Context triple: [Martha's Vineyard, hasLandArea, approximately 260 square kilometers]
-
A.
landArea
chosen
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
B.
hasOverseasTerritory
Indicates that one entity possesses or controls a territory located outside its own primary geographic or sovereign domain.
-
C.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
D.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
E.
hasCoastlineOn
Indicates that one entity’s coastline borders or is directly adjacent to a specified body of water.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.