Triple

T9522967
Position Surface form Disambiguated ID Type / Status
Subject United Evangelical Lutheran Church of Germany E229688 entity
Predicate abbreviation P43 FINISHED
Object VELKD
VELKD is a federation of Lutheran regional churches in Germany that coordinates theology, worship, and church life among its member churches.
 E803993 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: VELKD | Statement: [United Evangelical Lutheran Church of Germany, abbreviation, VELKD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VELKD
Context triple: [United Evangelical Lutheran Church of Germany, abbreviation, VELKD]
  • A. VLKK
    VLKK is the abbreviation for the State Commission of the Lithuanian Language, the official regulatory body overseeing the Lithuanian language.
  • B. LEVD
    LEVD is the ICAO airport code assigned to Valladolid Airport in Spain.
  • C. VLKSM
    VLKSM was the Russian abbreviation for the All-Union Leninist Young Communist League, the Soviet Union’s official youth organization affiliated with the Communist Party.
  • D. VILK
    VILK is the ICAO airport code for Chaudhary Charan Singh International Airport serving Lucknow, India.
  • E. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • 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: VELKD
Triple: [United Evangelical Lutheran Church of Germany, abbreviation, VELKD]
Generated description
VELKD is a federation of Lutheran regional churches in Germany that coordinates theology, worship, and church life among its member churches.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VELKD
Target entity description: VELKD is a federation of Lutheran regional churches in Germany that coordinates theology, worship, and church life among its member churches.
  • A. VLKK
    VLKK is the abbreviation for the State Commission of the Lithuanian Language, the official regulatory body overseeing the Lithuanian language.
  • B. LEVD
    LEVD is the ICAO airport code assigned to Valladolid Airport in Spain.
  • C. VLKSM
    VLKSM was the Russian abbreviation for the All-Union Leninist Young Communist League, the Soviet Union’s official youth organization affiliated with the Communist Party.
  • D. VILK
    VILK is the ICAO airport code for Chaudhary Charan Singh International Airport serving Lucknow, India.
  • E. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • 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_69ca847870a881909d8d751a7d29da39 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9898e0b48190a3e3f0f1616d5055 completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a61fbd08190bb68ffe29da3a34a completed April 4, 2026, 4:20 p.m.
NEDg Description generation batch_69d13c0344388190aefc18936b17b9f0 completed April 4, 2026, 4:27 p.m.
NED2 Entity disambiguation (via description) batch_69d13c7b2954819096a276e083d4fed1 completed April 4, 2026, 4:29 p.m.
Created at: March 30, 2026, 7:59 p.m.