Triple

T37805334
Position Surface form Disambiguated ID Type / Status
Subject Atlas Mugged E942484 entity
Predicate featuresCharacter P626 FINISHED
Object Sasha
Sasha is a supporting character in the Borderlands 2 DLC episode "Atlas Mugged" from the episodic game Tales from the Borderlands.
E942489 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: Sasha | Statement: [Atlas Mugged, featuresCharacter, Sasha]
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: Sasha
Triple: [Atlas Mugged, featuresCharacter, Sasha]
Generated description
Sasha is a supporting character in the Borderlands 2 DLC episode "Atlas Mugged" from the episodic game Tales from the Borderlands.

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_69fbb197983c8190b367cf4a5486bd13 completed May 6, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40f18d9f548190836fa632477ece60 completed June 28, 2026, 10:03 a.m.
NEDg Description generation batch_6a40f22972e48190a673737cf741e5aa completed June 28, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a40f2aa79808190a3952e3cade199a1 completed June 28, 2026, 10:08 a.m.
Created at: May 3, 2026, 4:19 p.m.