Triple

T28899341
Position Surface form Disambiguated ID Type / Status
Subject Metro City E732909 entity
Predicate partOfUniverse P15645 FINISHED
Object Street Fighter universe
The Street Fighter universe is a fictional world centered on global martial arts tournaments and diverse fighters, spanning numerous video games, comics, and other media.
E1841044 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: Street Fighter universe | Statement: [Metro City, partOfUniverse, Street Fighter universe]
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: Street Fighter universe
Triple: [Metro City, partOfUniverse, Street Fighter universe]
Generated description
The Street Fighter universe is a fictional world centered on global martial arts tournaments and diverse fighters, spanning numerous video games, comics, and other media.

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_69f05b08c2008190ac426a035a2ed66d completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65aa677948190ab5b5a097d4cea5d completed May 2, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec34a9948190a1ee692c79e8ff5d completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24eeb3c3008190b4ce860d20ed4c67 completed June 7, 2026, 4:08 a.m.
NED2 Entity disambiguation (via description) batch_6a24ef0945d88190939fbcfa77f6131d completed June 7, 2026, 4:09 a.m.
Created at: April 28, 2026, 8:01 a.m.