Triple

T21719221
Position Surface form Disambiguated ID Type / Status
Subject BBDO E536109 entity
Predicate notableClient P7186 FINISHED
Object GE
GE (General Electric) is a multinational conglomerate known for its operations in aviation, power, renewable energy, and healthcare technologies.
E1497878 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: GE | Statement: [BBDO, notableClient, GE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GE
Context triple: [BBDO, notableClient, GE]
  • A. GE
    GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
  • B. GE
    GE is the commonly used abbreviation for Global Entry, a U.S. government program that provides expedited clearance for pre-approved, low-risk international travelers entering the United States.
  • C. GE
    GE is the Swiss canton code for Geneva, a major city and canton in western Switzerland known for its international organizations and financial center.
  • D. GE
    GE is the abbreviation for ICANN’s Government Engagement function, which manages and coordinates ICANN’s relationships and interactions with governments and intergovernmental organizations worldwide.
  • E. GM
    GM is the station code used to identify GMA Kamuning station in the Manila Metro Rail Transit system.
  • 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: GE
Triple: [BBDO, notableClient, GE]
Generated description
GE (General Electric) is a multinational conglomerate known for its operations in aviation, power, renewable energy, and healthcare technologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: GE
Target entity description: GE (General Electric) is a multinational conglomerate known for its operations in aviation, power, renewable energy, and healthcare technologies.
  • A. GE
    GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
  • B. GE
    GE is the Swiss canton code for Geneva, a major city and canton in western Switzerland known for its international organizations and financial center.
  • C. GE
    GE is the abbreviation for ICANN’s Government Engagement function, which manages and coordinates ICANN’s relationships and interactions with governments and intergovernmental organizations worldwide.
  • D. GE
    GE is the commonly used abbreviation for Global Entry, a U.S. government program that provides expedited clearance for pre-approved, low-risk international travelers entering the United States.
  • E. GM
    GM is the vehicle registration code used on license plates for vehicles registered in the Oberbergischer Kreis district in North Rhine-Westphalia, Germany.
  • 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_69e0c46c6dd88190a595375fa6ebd701 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efd96cc58081908dda09819041b888 completed April 27, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a24b79c108190af57665372a88c2c completed May 17, 2026, 8:27 p.m.
NEDg Description generation batch_6a0a2698fb408190b0ad72d4fdb74ded completed May 17, 2026, 8:35 p.m.
NED2 Entity disambiguation (via description) batch_6a0a274893d8819084c55439fe1eb686 completed May 17, 2026, 8:38 p.m.
Created at: April 16, 2026, 6:47 p.m.