Triple

T25797428
Position Surface form Disambiguated ID Type / Status
Subject Inglourious Basterds (commando unit) E649724 entity
Predicate memberInFiction P104242 FINISHED
Object Hugo Stiglitz
Hugo Stiglitz is a ruthless former German sergeant turned Nazi-killing vigilante and later Allied commando in Quentin Tarantino’s film "Inglourious Basterds."
E1693759 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: Hugo Stiglitz | Statement: [Inglourious Basterds (commando unit), memberInFiction, Hugo Stiglitz]
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: Hugo Stiglitz
Triple: [Inglourious Basterds (commando unit), memberInFiction, Hugo Stiglitz]
Generated description
Hugo Stiglitz is a ruthless former German sergeant turned Nazi-killing vigilante and later Allied commando in Quentin Tarantino’s film "Inglourious Basterds."

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_69e7ab34f8c8819099f6c4dabdabf129 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f67e4586988190ad89b72dd2af3797 completed May 2, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cc316dbc8190bdbdb62a13e75f57 completed May 22, 2026, 9:35 p.m.
NEDg Description generation batch_6a10ccee67b881908f933ec91168f098 completed May 22, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_6a10cdf9537481909131c59b126e69b6 completed May 22, 2026, 9:43 p.m.
Created at: April 22, 2026, 6:32 a.m.