Triple

T14608921
Position Surface form Disambiguated ID Type / Status
Subject Georges Bataille E342904 entity
Predicate placeOfBirth P1 FINISHED
Object Billom
Billom is a small historic town in central France’s Auvergne region, known for its medieval architecture and traditional markets.
E1108389 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: Billom | Statement: [Georges Bataille, placeOfBirth, Billom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Billom
Context triple: [Georges Bataille, placeOfBirth, Billom]
  • A. Billiri
    Billiri is a town and administrative center in northeastern Nigeria known for serving as one of the local government areas within Gombe State.
  • B. Bille
    The Bille is a small river in northern Germany that flows through the city of Hamburg and into the Elbe.
  • C. Billinudgel
    Billinudgel is a small rural village in the Northern Rivers region of New South Wales, Australia, known for its historic pub and laid-back country atmosphere.
  • D. Al Luginbill
    Al Luginbill is an American football coach best known for his leadership roles in NFL Europe and college football programs.
  • E. Blix
    Blix is a 19th-century novel by American naturalist writer Frank Norris that follows a young woman’s coming-of-age and romantic experiences in San Francisco.
  • 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: Billom
Triple: [Georges Bataille, placeOfBirth, Billom]
Generated description
Billom is a small historic town in central France’s Auvergne region, known for its medieval architecture and traditional markets.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Billom
Target entity description: Billom is a small historic town in central France’s Auvergne region, known for its medieval architecture and traditional markets.
  • A. Billiri
    Billiri is a town and administrative center in northeastern Nigeria known for serving as one of the local government areas within Gombe State.
  • B. Bille
    The Bille is a small river in northern Germany that flows through the city of Hamburg and into the Elbe.
  • C. Billinudgel
    Billinudgel is a small rural village in the Northern Rivers region of New South Wales, Australia, known for its historic pub and laid-back country atmosphere.
  • D. Al Luginbill
    Al Luginbill is an American football coach best known for his leadership roles in NFL Europe and college football programs.
  • E. Blix
    Blix is a 19th-century novel by American naturalist writer Frank Norris that follows a young woman’s coming-of-age and romantic experiences in San Francisco.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44f0dd48190a78662b5998a6722 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94d09e988190a2a2a1332397b412 completed May 8, 2026, 7:46 a.m.
NEDg Description generation batch_69fd9828129c8190bd7445e99dadc618 completed May 8, 2026, 8 a.m.
NED2 Entity disambiguation (via description) batch_69fd98cf0bcc81909dac826a32daaf04 completed May 8, 2026, 8:03 a.m.
Created at: April 10, 2026, 1:25 a.m.