Triple
T20139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlestown, Massachusetts Bay Colony |
E399
|
entity |
| Predicate | terrain |
P940
|
FINISHED |
| Object | peninsula |
—
|
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: peninsula | Statement: [Charlestown, Massachusetts Bay Colony, terrain, peninsula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrain Context triple: [Charlestown, Massachusetts Bay Colony, terrain, peninsula]
-
A.
surfaceType
Indicates the kind or classification of surface associated with an entity or interaction.
-
B.
hasLandform
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
C.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
D.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
E.
continent
Indicates that one entity is a continent on which the other entity is geographically located or to which it belongs.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.