Triple
T10503346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin (Sin City) |
E247724
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Basin City |
E237843
|
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: Basin City | Statement: [Kevin (Sin City), basedIn, Basin City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Basin City Context triple: [Kevin (Sin City), basedIn, Basin City]
-
A.
Basin City
chosen
Basin City is the gritty, crime-ridden fictional metropolis that serves as the primary setting for Frank Miller’s Sin City graphic novels and their film adaptations.
-
B.
Limestone City
Limestone City is a nickname for Kingston, Ontario, reflecting its many historic buildings constructed from local limestone.
-
C.
Barb City
Barb City is the nickname of DeKalb, Illinois, reflecting its historical prominence in the barbed wire industry.
-
D.
Lumber City
Lumber City is a small rural town in south-central Georgia, United States, known historically for its timber industry and location near the confluence of the Ocmulgee and Oconee rivers.
-
E.
Ice City
Ice City is the popular nickname for Harbin, a major northeastern Chinese city renowned for its frigid winters and spectacular ice and snow sculptures.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099d62408190a6c6884411c6e423 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d933d4b63081909ad297038fb74bed |
completed | April 10, 2026, 5:31 p.m. |
Created at: April 6, 2026, 12:25 p.m.