Triple

T30734361
Position Surface form Disambiguated ID Type / Status
Subject Max Payne E782506 entity
Predicate hasSequel P1961 FINISHED
Object Max Payne 3
Max Payne 3 is a third-person neo-noir action shooter developed by Rockstar Games that follows former detective Max Payne through a violent, cinematic story of corruption and revenge in Brazil.
E1932671 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: Max Payne 3 | Statement: [Max Payne, hasSequel, Max Payne 3]
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: Max Payne 3
Triple: [Max Payne, hasSequel, Max Payne 3]
Generated description
Max Payne 3 is a third-person neo-noir action shooter developed by Rockstar Games that follows former detective Max Payne through a violent, cinematic story of corruption and revenge in Brazil.

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_69f224ad9f9c81908e02a79ae0001137 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68ee54d1c8190a4c020394f7fb19a completed May 2, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbcea6448190b24c401b476f8c8d completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bc580ea08190848e95bff35a2ab0 completed June 10, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a28bcf1f5d081908823910cd023c991 completed June 10, 2026, 1:25 a.m.
Created at: April 29, 2026, 8:37 p.m.