Triple

T4045459
Position Surface form Disambiguated ID Type / Status
Subject Berg en Dal E84054 entity
Predicate contains P35 FINISHED
Object Erlecom
Erlecom is a small village in the Dutch province of Gelderland, situated along the Waal River within the municipality of Berg en Dal.
 E408457 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: Erlecom | Statement: [Berg en Dal, contains, Erlecom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Erlecom
Context triple: [Berg en Dal, contains, Erlecom]
  • A. Telefunken
    Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
  • B. Volacom
    Volacom is a company founded by Tesla co-founder and battery technology pioneer JB Straubel, likely focused on advanced engineering and sustainable technology solutions.
  • C. Elxsi
    Elxsi was a computer company known for developing high-performance minicomputers and multiprocessor systems in the late 20th century.
  • D. Fitel
    Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
  • E. Teldec
    Teldec was a prominent German classical music record label known for its high-quality recordings and influential catalog of orchestral and early music.
  • 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: Erlecom
Triple: [Berg en Dal, contains, Erlecom]
Generated description
Erlecom is a small village in the Dutch province of Gelderland, situated along the Waal River within the municipality of Berg en Dal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Erlecom
Target entity description: Erlecom is a small village in the Dutch province of Gelderland, situated along the Waal River within the municipality of Berg en Dal.
  • A. Telefunken
    Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
  • B. Volacom
    Volacom is a company founded by Tesla co-founder and battery technology pioneer JB Straubel, likely focused on advanced engineering and sustainable technology solutions.
  • C. Elxsi
    Elxsi was a computer company known for developing high-performance minicomputers and multiprocessor systems in the late 20th century.
  • D. Fitel
    Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
  • E. Teldec
    Teldec was a prominent German classical music record label known for its high-quality recordings and influential catalog of orchestral and early music.
  • 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_69aed930bd5c819083e7dcc14fc44f69 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb5f85d48190ba80a0a24fbe438a completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55652228c8190a9f301676deb0055 completed March 14, 2026, 12:36 p.m.
NEDg Description generation batch_69b556fec4708190b221893ec35f1a38 completed March 14, 2026, 12:39 p.m.
NED2 Entity disambiguation (via description) batch_69b557f73cbc8190b904089ab0fa97d6 completed March 14, 2026, 12:43 p.m.
Created at: March 9, 2026, 3:37 p.m.