Triple
T19535588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regional at Best |
E488758
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Forest |
—
|
NE NERFINISHED |
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: Forest | Statement: [Regional at Best, hasPart, Forest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Forest Context triple: [Regional at Best, hasPart, Forest]
-
A.
Forest
Forest is the central protagonist of the game *Devs*, around whom the story’s main events and character dynamics revolve.
-
B.
Forest
chosen
Forest is a municipality in the Brussels-Capital Region of Belgium, known for its mix of residential areas, green spaces, and cultural venues.
-
C.
Woodland
Woodland is a small city located in Talbot County, Georgia, in the United States.
-
D.
Woodland
Woodland is a small rural community located in the state of Maine in the United States.
-
E.
Woodland
Woodland is a light rail station on Boston’s MBTA Green Line D branch serving the Newton area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6386ddc208190962195b8aa568bed |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.