Triple

T16011687
Position Surface form Disambiguated ID Type / Status
Subject Peter Watts E388349 entity
Predicate authorOf P4244 FINISHED
Object βehemoth: β-Max
βehemoth: β-Max is a hard science fiction novel by Peter Watts that continues his dark, bioengineered post-apocalyptic Behemoth storyline.
E1189418 NE FINISHED

How this triple was built (4 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: βehemoth: β-Max | Statement: [Peter Watts, authorOf, βehemoth: β-Max]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: βehemoth: β-Max
Context triple: [Peter Watts, authorOf, βehemoth: β-Max]
  • A. BHE
    BHE is the station code for Berlin-Hermsdorf railway station in Berlin, Germany.
  • B. BFEH
    BFEH is the German Federal Office dedicated to promoting and safeguarding the equal rights and inclusion of people with disabilities.
  • C. BMH
    BMH is the National Rail station code for Bournemouth railway station in Dorset, England.
  • D. BHB
    BHB is the stock exchange of the Kingdom of Bahrain, providing a regulated marketplace for trading securities and other financial instruments.
  • E. BEM
    BEM is the post-nominal abbreviation for the British Empire Medal, an honor awarded for meritorious civil or military service in the United Kingdom and Commonwealth.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: βehemoth: β-Max
Triple: [Peter Watts, authorOf, βehemoth: β-Max]
Generated description
βehemoth: β-Max is a hard science fiction novel by Peter Watts that continues his dark, bioengineered post-apocalyptic Behemoth storyline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: βehemoth: β-Max
Target entity description: βehemoth: β-Max is a hard science fiction novel by Peter Watts that continues his dark, bioengineered post-apocalyptic Behemoth storyline.
  • A. BHE
    BHE is the station code for Berlin-Hermsdorf railway station in Berlin, Germany.
  • B. BFEH
    BFEH is the German Federal Office dedicated to promoting and safeguarding the equal rights and inclusion of people with disabilities.
  • C. BMH
    BMH is the National Rail station code for Bournemouth railway station in Dorset, England.
  • D. BHB
    BHB is the stock exchange of the Kingdom of Bahrain, providing a regulated marketplace for trading securities and other financial instruments.
  • E. BEM
    BEM is the post-nominal abbreviation for the British Empire Medal, an honor awarded for meritorious civil or military service in the United Kingdom and Commonwealth.
  • F. None of above. chosen

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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1829119648190aef5b5e84b26d898 completed April 17, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf267a9c81908f1fa1ad117c5e2c completed May 10, 2026, 12:19 a.m.
NEDg Description generation batch_69ffd0bfc05881908d7223c52050ea14 completed May 10, 2026, 12:26 a.m.
NED2 Entity disambiguation (via description) batch_69ffd159dbcc81908ac586a6b8de57cf completed May 10, 2026, 12:29 a.m.
Created at: April 10, 2026, 4:55 a.m.