Triple
T8552065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fatal Fury: King of Fighters |
E202466
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object |
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.
|
E741476
|
NE FINISHED |
How this triple was built (4 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: South Town | Statement: [Fatal Fury: King of Fighters, setting, South Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: South Town Context triple: [Fatal Fury: King of Fighters, setting, South Town]
-
A.
B-Town
B-Town is a common nickname for Bloomington, Indiana, a vibrant Midwestern college city best known as the home of Indiana University.
-
B.
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.
-
C.
Cross Town
Cross Town is a residential neighbourhood within the town of Knutsford in Cheshire, England.
-
D.
Outer City
The Outer City was the extensive outer urban area surrounding the central core of Dadu, the Yuan dynasty capital later known as Beijing.
-
E.
Sand City
Sand City is a small coastal city in Monterey County, California, known for its beaches, sand dunes, and outlet shopping.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: South Town Triple: [Fatal Fury: King of Fighters, setting, South Town]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: South Town Target entity description: 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.
-
A.
B-Town
B-Town is a common nickname for Bloomington, Indiana, a vibrant Midwestern college city best known as the home of Indiana University.
-
B.
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.
-
C.
Cross Town
Cross Town is a residential neighbourhood within the town of Knutsford in Cheshire, England.
-
D.
Outer City
The Outer City was the extensive outer urban area surrounding the central core of Dadu, the Yuan dynasty capital later known as Beijing.
-
E.
Sand City
Sand City is a small coastal city in Monterey County, California, known for its beaches, sand dunes, and outlet shopping.
- F. None of above. chosen
Provenance (5 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe886fb788190a73e7c76c4f86409 |
completed | March 31, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6dc7f6fc8190addd5d2bbe1f4408 |
completed | April 2, 2026, 1:23 p.m. |
| NEDg | Description generation | batch_69ce6f3f40708190a351600ec9f12ee4 |
completed | April 2, 2026, 1:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce703b74f8819093bda2d3e59f7e94 |
completed | April 2, 2026, 1:33 p.m. |
Created at: March 30, 2026, 6:19 p.m.