Triple
T10620471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloomington, Indiana |
E250183
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | B-Town |
E250183
|
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: B-Town | Statement: [Bloomington, Indiana, nickname, B-Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: B-Town Context triple: [Bloomington, Indiana, nickname, B-Town]
-
A.
B-Town
chosen
B-Town is a common nickname for Bloomington, Indiana, a vibrant Midwestern college city best known as the home of Indiana University.
-
B.
South Town
South Town is a fictional, crime-ridden American metropolis that serves as the primary backdrop for SNK’s Fatal Fury and related fighting game series.
-
C.
L-Town
L-Town is a colloquial nickname for Lansing, the capital city of the U.S. state of Michigan.
-
D.
Red Town
Red Town is a historical region associated with the settlement of Krasnaya Sloboda, known for its cultural and regional significance.
-
E.
Mob Town
Mob Town is a historic nickname for the city of Baltimore, reflecting its long-standing reputation for civil unrest and rowdy public gatherings in the 19th century.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df6fc47c8190b77b61a7fd223d65 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b86a5bc8190863034cc91fdbbb9 |
completed | April 10, 2026, 9:28 p.m. |
Created at: April 8, 2026, 8:46 p.m.