Triple

T40802
Position Surface form Disambiguated ID Type / Status
Subject Angela Merkel E805 entity
Predicate givenName P17 FINISHED
Object Angela
Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
 E10812 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: Angela | Statement: [Angela Merkel, givenName, Angela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Angela
Context triple: [Angela Merkel, givenName, Angela]
  • A. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • B. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • C. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • D. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • E. Maia
    Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
  • 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: Angela
Triple: [Angela Merkel, givenName, Angela]
Generated description
Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Angela
Target entity description: Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
  • A. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • B. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • C. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • D. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • E. Maia
    Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ae0b7c4819092220568e8e52ad5 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a275df03dc81908c338b656feb9635 completed Feb. 28, 2026, 4:58 a.m.
NEDg Description generation batch_69a2770e91e081908c717b4a449e0a3e completed Feb. 28, 2026, 5:03 a.m.
NED2 Entity disambiguation (via description) batch_69a278a3b7f88190b10bf9d74cb68282 completed Feb. 28, 2026, 5:09 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.