Triple

T3668748
Position Surface form Disambiguated ID Type / Status
Subject Beno Gutenberg E77826 entity
Predicate givenName P17 FINISHED
Object Beno
Beno is the given name of the German seismologist Beno Gutenberg, known for his pioneering work on the structure of the Earth's interior.
 E377369 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: Beno | Statement: [Beno Gutenberg, givenName, Beno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Beno
Context triple: [Beno Gutenberg, givenName, Beno]
  • A. Bernardin
    Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
  • B. Bènizàa
    Bènizàa is the self-designation used by a Zapotec people of Oaxaca, Mexico, reflecting their own name and identity distinct from the externally applied term "Zapotec."
  • C. Bittou
    Bittou is a town in Burkina Faso known for its role as a regional trading center and its international town-twinning links with European municipalities.
  • D. Bongrand
    Bongrand is a fictional character in Émile Zola’s novel *L’Œuvre*, depicted as an older, established painter who contrasts with the avant-garde ambitions of the protagonist.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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: Beno
Triple: [Beno Gutenberg, givenName, Beno]
Generated description
Beno is the given name of the German seismologist Beno Gutenberg, known for his pioneering work on the structure of the Earth's interior.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Beno
Target entity description: Beno is the given name of the German seismologist Beno Gutenberg, known for his pioneering work on the structure of the Earth's interior.
  • A. Bernardin
    Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
  • B. Bènizàa
    Bènizàa is the self-designation used by a Zapotec people of Oaxaca, Mexico, reflecting their own name and identity distinct from the externally applied term "Zapotec."
  • C. Bittou
    Bittou is a town in Burkina Faso known for its role as a regional trading center and its international town-twinning links with European municipalities.
  • D. Bongrand
    Bongrand is a fictional character in Émile Zola’s novel *L’Œuvre*, depicted as an older, established painter who contrasts with the avant-garde ambitions of the protagonist.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc42997d88190bc765559bd7645fc completed March 8, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4884e36108190a19887e81921fe32 completed March 13, 2026, 9:57 p.m.
NEDg Description generation batch_69b48aa728fc8190b1a4e4d6d466efb5 completed March 13, 2026, 10:07 p.m.
NED2 Entity disambiguation (via description) batch_69b4af0410e8819091cb1259d06d60cc completed March 14, 2026, 12:42 a.m.
Created at: March 8, 2026, 3:25 p.m.