Triple

T37803686
Position Surface form Disambiguated ID Type / Status
Subject Santa Monica Studio E942447 entity
Predicate notableWork P4 FINISHED
Object God of War II
God of War II is an action-adventure hack-and-slash video game in the God of War series, known for its cinematic storytelling, brutal combat, and Greek mythology-inspired setting.
E2245557 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: God of War II | Statement: [Santa Monica Studio, notableWork, God of War 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: God of War II
Triple: [Santa Monica Studio, notableWork, God of War II]
Generated description
God of War II is an action-adventure hack-and-slash video game in the God of War series, known for its cinematic storytelling, brutal combat, and Greek mythology-inspired setting.

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_69f76ee8104c8190ab17133ccd8f86e6 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb177dcf081909ac46fbcc787cd4f completed May 6, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40fb7744c88190bbe8f7e453ba263e completed June 28, 2026, 10:46 a.m.
NEDg Description generation batch_6a40fc1014b481909d49228689c8a7d7 completed June 28, 2026, 10:48 a.m.
NED2 Entity disambiguation (via description) batch_6a40fd1546c081909e9ceebadb9ef51a completed June 28, 2026, 10:53 a.m.
Created at: May 3, 2026, 4:19 p.m.