Triple

T29248068
Position Surface form Disambiguated ID Type / Status
Subject Nakoruru E741489 entity
Predicate appearsIn P795 FINISHED
Object Samurai Shodown II
Samurai Shodown II is a 1994 weapon-based fighting game by SNK for arcades and Neo Geo, widely regarded as one of the best entries in the Samurai Shodown series for its refined mechanics and diverse roster.
E1880028 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: Samurai Shodown II | Statement: [Nakoruru, appearsIn, Samurai Shodown II]
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: Samurai Shodown II
Triple: [Nakoruru, appearsIn, Samurai Shodown II]
Generated description
Samurai Shodown II is a 1994 weapon-based fighting game by SNK for arcades and Neo Geo, widely regarded as one of the best entries in the Samurai Shodown series for its refined mechanics and diverse roster.

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_69f0911eba2c8190b07cd2fdf91422c9 completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f6648b128c81908bff08760a8877d4 completed May 2, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267e939ee88190bb3572a603b5571d completed June 8, 2026, 8:34 a.m.
NEDg Description generation batch_6a26897ca98481908b79e5d92ec24714 completed June 8, 2026, 9:21 a.m.
NED2 Entity disambiguation (via description) batch_6a268d4658cc8190b80c1390b8763960 completed June 8, 2026, 9:37 a.m.
Created at: April 28, 2026, 12:33 p.m.