Triple
T2729251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hartford County |
E60269
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Vernon |
E287590
|
NE 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: Vernon | Statement: [Hartford County, hasCity, Vernon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vernon Context triple: [Hartford County, hasCity, Vernon]
-
A.
Vernon
Vernon is a town in northern France on the Seine River, known for its picturesque setting that attracted artists such as Pierre Bonnard.
-
B.
Vernon
Vernon is a small, heavily industrial city located just south of downtown Los Angeles in Southern California.
-
C.
Vernon
chosen
Vernon is a suburban town in north-central Connecticut that forms part of the Greater Hartford metropolitan area.
-
D.
Linwood
Linwood is a small Scottish town in Renfrewshire, near Paisley, known historically for its car manufacturing and as a residential commuter community for the Greater Glasgow area.
-
E.
Winslow
Winslow is the main commercial and residential hub of Bainbridge Island, Washington, known for its downtown shops, restaurants, and ferry terminal connecting to Seattle.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaeaee388190a21e7fa0b8f83546 |
completed | March 7, 2026, 7:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb69aa8b081909c57e8a7f64d0913 |
completed | March 10, 2026, 6:13 a.m. |
Created at: March 6, 2026, 9:56 p.m.