Triple

T13351705
Position Surface form Disambiguated ID Type / Status
Subject Behmen von Bleibruck E318084 entity
Predicate givenName P17 FINISHED
Object Behmen
Behmen is the given name of Behmen von Bleibruck, a historical figure likely associated with German-speaking Central Europe.
 E1034754 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: Behmen | Statement: [Behmen von Bleibruck, givenName, Behmen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Behmen
Context triple: [Behmen von Bleibruck, givenName, Behmen]
  • A. Mahneshan
    Mahneshan is a small city in northwestern Iran known for its rural surroundings and location within Zanjan Province.
  • B. Behdini
    Behdini is a Northern Kurdish (Kurmanji) dialect spoken primarily by Kurdish communities in and around the Dohuk region of Iraqi Kurdistan.
  • C. Farmanieh
    Farmanieh is an affluent, upscale neighborhood in northern Tehran known for its luxury residences, embassies, and high-end amenities.
  • D. Kalaleh
    Kalaleh is a city in northeastern Iran known as a local administrative and agricultural center.
  • E. Azarbarzin
    Azarbarzin is a character from Persian epic tradition, known primarily as the son of the legendary hero Esfandiyar.
  • 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: Behmen
Triple: [Behmen von Bleibruck, givenName, Behmen]
Generated description
Behmen is the given name of Behmen von Bleibruck, a historical figure likely associated with German-speaking Central Europe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Behmen
Target entity description: Behmen is the given name of Behmen von Bleibruck, a historical figure likely associated with German-speaking Central Europe.
  • A. Mahneshan
    Mahneshan is a small city in northwestern Iran known for its rural surroundings and location within Zanjan Province.
  • B. Behdini
    Behdini is a Northern Kurdish (Kurmanji) dialect spoken primarily by Kurdish communities in and around the Dohuk region of Iraqi Kurdistan.
  • C. Farmanieh
    Farmanieh is an affluent, upscale neighborhood in northern Tehran known for its luxury residences, embassies, and high-end amenities.
  • D. Kalaleh
    Kalaleh is a city in northeastern Iran known as a local administrative and agricultural center.
  • E. Azarbarzin
    Azarbarzin is a character from Persian epic tradition, known primarily as the son of the legendary hero Esfandiyar.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8c2f1c819094f0970f35f18afa completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f47fd7c8190b8d98a181acd7710 completed May 3, 2026, 10:11 a.m.
NEDg Description generation batch_69f7204b6f108190bca6a0140620e03e completed May 3, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_69f720fbf0bc81908c68cf2844938e45 completed May 3, 2026, 10:18 a.m.
Created at: April 9, 2026, 9:32 p.m.