Triple
T22529462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myles Standish |
E556994
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Standish |
—
|
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: Standish | Statement: [Myles Standish, familyName, Standish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Standish Context triple: [Myles Standish, familyName, Standish]
-
A.
Standish
Standish is a village in Lancashire, England, known for its historic parish church and traditional English character.
-
B.
Standish
chosen
Standish is an English surname historically associated with several notable families and figures in Britain.
-
C.
Standish
Standish is a small unincorporated rural community located in Lassen County in northeastern California.
-
D.
Brainerd
Brainerd is a small city in central Minnesota, United States, known as a regional hub for outdoor recreation in the lakes area.
-
E.
Standish, Maine
Standish, Maine is a small town in southern Maine known for its rural character, lakeside recreation on Sebago Lake, and proximity to the Portland metropolitan 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed5b5d081909d927f8aee44b673 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.