Triple

T15844046
Position Surface form Disambiguated ID Type / Status
Subject Federal Office of Communications E384169 entity
Predicate shortName P43 FINISHED
Object BAKOM
BAKOM is the Swiss Federal Office of Communications, the national authority responsible for regulating telecommunications, broadcasting, and related communication services in Switzerland.
 E1179781 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: BAKOM | Statement: [Federal Office of Communications, shortName, BAKOM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BAKOM
Context triple: [Federal Office of Communications, shortName, BAKOM]
  • A. BAK
    BAK is the acronym for the Swiss Federal Office of Culture, the national authority responsible for promoting and preserving Switzerland’s cultural heritage and arts.
  • B. BAK
    BAK is the National Rail station code used to identify Baker Street station in London’s rail network.
  • C. BAKIZA
    BAKIZA is the official Swahili language council of Zanzibar responsible for promoting, standardizing, and developing Kiswahili in the region.
  • D. BOK
    BOK is the station code for Berlin Ostkreuz, a major railway interchange in Berlin, Germany.
  • E. BOK
    BOK is the commonly used nickname for the BOK Center, a major multi-purpose arena in Tulsa, Oklahoma.
  • 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: BAKOM
Triple: [Federal Office of Communications, shortName, BAKOM]
Generated description
BAKOM is the Swiss Federal Office of Communications, the national authority responsible for regulating telecommunications, broadcasting, and related communication services in Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BAKOM
Target entity description: BAKOM is the Swiss Federal Office of Communications, the national authority responsible for regulating telecommunications, broadcasting, and related communication services in Switzerland.
  • A. BAK
    BAK is the acronym for the Swiss Federal Office of Culture, the national authority responsible for promoting and preserving Switzerland’s cultural heritage and arts.
  • B. BAK
    BAK is the National Rail station code used to identify Baker Street station in London’s rail network.
  • C. BAKIZA
    BAKIZA is the official Swahili language council of Zanzibar responsible for promoting, standardizing, and developing Kiswahili in the region.
  • D. BOK
    BOK is the station code for Berlin Ostkreuz, a major railway interchange in Berlin, Germany.
  • E. BOK
    BOK is the commonly used nickname for the BOK Center, a major multi-purpose arena in Tulsa, Oklahoma.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142eb20088190bb45e37ce3291ef2 completed April 16, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa1412c9481909808473e14058033 completed May 9, 2026, 9:04 p.m.
NEDg Description generation batch_69ffa419c6dc81908c9678f8434530f8 completed May 9, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69ffa4cff5088190a7f11fd62941f4fb completed May 9, 2026, 9:19 p.m.
Created at: April 10, 2026, 4:50 a.m.