Triple

T2272981
Position Surface form Disambiguated ID Type / Status
Subject Emer de Vattel E50702 entity
Predicate givenName P17 FINISHED
Object Emer
Emer is a given name most notably borne by the 18th-century Swiss legal philosopher Emer de Vattel, known for his influential work on international law.
 E250864 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: Emer | Statement: [Emer de Vattel, givenName, Emer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emer
Context triple: [Emer de Vattel, givenName, Emer]
  • A. Em
    Em is a common shortened form of the given name Emma, often used as an informal nickname.
  • B. Ent
    Ent is a surname most notably associated with Uzal G. Ent, a senior officer in the United States Army Air Forces during World War II.
  • C. ER
    ER is a critically acclaimed American medical drama television series that follows the personal and professional lives of staff in a busy Chicago emergency room.
  • D. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • E. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • 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: Emer
Triple: [Emer de Vattel, givenName, Emer]
Generated description
Emer is a given name most notably borne by the 18th-century Swiss legal philosopher Emer de Vattel, known for his influential work on international law.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emer
Target entity description: Emer is a given name most notably borne by the 18th-century Swiss legal philosopher Emer de Vattel, known for his influential work on international law.
  • A. Em
    Em is a common shortened form of the given name Emma, often used as an informal nickname.
  • B. Ent
    Ent is a surname most notably associated with Uzal G. Ent, a senior officer in the United States Army Air Forces during World War II.
  • C. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • D. ER
    ER is a critically acclaimed American medical drama television series that follows the personal and professional lives of staff in a busy Chicago emergency room.
  • E. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1e872448190a1d6c6071b2a294b completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71ddc66c81909525394a8b2bb4e0 completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae75ba1a988190ba59d3ce5e5c39a8 completed March 9, 2026, 7:24 a.m.
NED2 Entity disambiguation (via description) batch_69ae76246f6c81909a15262d2c4ea975 completed March 9, 2026, 7:26 a.m.
Created at: March 4, 2026, 7:48 p.m.