Triple

T18401215
Position Surface form Disambiguated ID Type / Status
Subject SPECTRE E449998 entity
Predicate notableMember P10 FINISHED
Object Franz Oberhauser
Franz Oberhauser is the primary antagonist in the James Bond film "Spectre," later revealed as Ernst Stavro Blofeld, the mastermind behind the global criminal organization SPECTRE.
E1997385 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: Franz Oberhauser | Statement: [SPECTRE, notableMember, Franz Oberhauser]
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: Franz Oberhauser
Triple: [SPECTRE, notableMember, Franz Oberhauser]
Generated description
Franz Oberhauser is the primary antagonist in the James Bond film "Spectre," later revealed as Ernst Stavro Blofeld, the mastermind behind the global criminal organization SPECTRE.

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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e5195185b08190bd3b5471cdc047b0 completed April 19, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2f3b5ad9ec81909a391e5f0da1d118 completed June 14, 2026, 11:38 p.m.
NEDg Description generation batch_6a2f3c6228388190ac68cfbe4aa06306 completed June 14, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_6a2f40454f3c81908fbc6be995ff5c07 completed June 14, 2026, 11:59 p.m.
Created at: April 10, 2026, 10:46 a.m.