Triple
T6000941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Flashes |
E133592
|
entity |
| Predicate | homeCity |
P263
|
FINISHED |
| Object | Kent, Ohio |
E156899
|
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: Kent, Ohio | Statement: [Golden Flashes, homeCity, Kent, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kent, Ohio Context triple: [Golden Flashes, homeCity, Kent, Ohio]
-
A.
Kent, Ohio
chosen
Kent, Ohio is a city in northeastern Ohio best known as the home of Kent State University.
-
B.
Kettering, Ohio
Kettering, Ohio is a suburban city near Dayton known for its residential communities, parks, and role as a commercial and cultural hub in the Miami Valley region.
-
C.
Oakland, Kentucky
Oakland, Kentucky is a small town in Warren County that functions as part of the broader Bowling Green regional community in south-central Kentucky.
-
D.
Bryan, Ohio
Bryan, Ohio is a small city in northwestern Ohio that serves as the county seat of Williams County.
-
E.
Montgomery, Ohio
Montgomery, Ohio is a suburban city in Hamilton County near Cincinnati, known for its historic charm, affluent residential character, and well-regarded schools.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04ee7c0e08190a6e78969448b070a |
completed | March 22, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e3a5d54c8190b2bc8b3291f8ac2f |
completed | March 27, 2026, 1:55 a.m. |
Created at: March 22, 2026, 4:05 p.m.