Triple

T16037803
Position Surface form Disambiguated ID Type / Status
Subject Aleida Assmann E389012 entity
Predicate familyName P18 FINISHED
Object Assmann
Assmann is a German surname borne by several notable figures, including scholars and public intellectuals.
 E1190974 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: Assmann | Statement: [Aleida Assmann, familyName, Assmann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Assmann
Context triple: [Aleida Assmann, familyName, Assmann]
  • A. Bockelmann
    Bockelmann is the birth surname of Austrian-Swiss composer and singer Udo Jürgens.
  • B. Verner
    Verner is a given name and surname of Germanic origin, used in various European countries.
  • C. Gimbutas
    Gimbutas is a Lithuanian surname most prominently associated with Marija Gimbutas, the influential archaeologist known for her work on Neolithic and Bronze Age cultures of Old Europe.
  • D. Andreae
    Andreae is a German surname historically associated with notable theologians and scholars, particularly in the context of the Protestant Reformation.
  • E. Sambursky
    Sambursky is the surname of Shmuel Sambursky, an Israeli physicist and historian of science known for his work on the conceptual foundations of physics in antiquity and the Middle Ages.
  • 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: Assmann
Triple: [Aleida Assmann, familyName, Assmann]
Generated description
Assmann is a German surname borne by several notable figures, including scholars and public intellectuals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Assmann
Target entity description: Assmann is a German surname borne by several notable figures, including scholars and public intellectuals.
  • A. Bockelmann
    Bockelmann is the birth surname of Austrian-Swiss composer and singer Udo Jürgens.
  • B. Verner
    Verner is a given name and surname of Germanic origin, used in various European countries.
  • C. Gimbutas
    Gimbutas is a Lithuanian surname most prominently associated with Marija Gimbutas, the influential archaeologist known for her work on Neolithic and Bronze Age cultures of Old Europe.
  • D. Andreae
    Andreae is a German surname historically associated with notable theologians and scholars, particularly in the context of the Protestant Reformation.
  • E. Sambursky
    Sambursky is the surname of Shmuel Sambursky, an Israeli physicist and historian of science known for his work on the conceptual foundations of physics in antiquity and the Middle Ages.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1833da68881908710fb2c28e8c6d0 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbd5acb48190a10e40074fffd425 completed May 10, 2026, 1:13 a.m.
NEDg Description generation batch_69ffdd527cfc8190a616a2334edffd02 completed May 10, 2026, 1:20 a.m.
NED2 Entity disambiguation (via description) batch_69ffdda1a0908190b7c880c5d66f7400 completed May 10, 2026, 1:21 a.m.
Created at: April 10, 2026, 4:56 a.m.