Triple

T8090434
Position Surface form Disambiguated ID Type / Status
Subject Emperor Zhang of Han E188844 entity
Predicate givenName P17 FINISHED
Object Da
Da was the personal given name of Emperor Zhang, a ruler of the Eastern Han dynasty in ancient China.
 E711388 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: Da | Statement: [Emperor Zhang of Han, givenName, Da]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Da
Context triple: [Emperor Zhang of Han, givenName, Da]
  • A. DA
    DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
  • B. DA
    DA is a postcode area in southeast England covering parts of south-east London and northwest Kent, including towns such as Dartford and Sidcup.
  • C. DA
    DA is the vehicle registration code for the German city of Darmstadt and its surrounding district in the state of Hesse.
  • D. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • E. Dar
    Dar is the warrior protagonist and titular Beastmaster of the Beastmaster fantasy franchise, known for his ability to telepathically communicate with and command animals.
  • 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: Da
Triple: [Emperor Zhang of Han, givenName, Da]
Generated description
Da was the personal given name of Emperor Zhang, a ruler of the Eastern Han dynasty in ancient China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Da
Target entity description: Da was the personal given name of Emperor Zhang, a ruler of the Eastern Han dynasty in ancient China.
  • A. DA
    DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
  • B. DA
    DA is a postcode area in southeast England covering parts of south-east London and northwest Kent, including towns such as Dartford and Sidcup.
  • C. DA
    DA is the vehicle registration code for the German city of Darmstadt and its surrounding district in the state of Hesse.
  • D. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • E. Dar
    Dar is the warrior protagonist and titular Beastmaster of the Beastmaster fantasy franchise, known for his ability to telepathically communicate with and command animals.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb421fb8348190b6495394d498d3f4 completed March 31, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc640a42648190bc1a3072eb338e22 completed April 1, 2026, 12:17 a.m.
NEDg Description generation batch_69cc68d9032c8190af6c5ff64fe46aff completed April 1, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_69cc69f6bb308190a95df95d1a67cfec completed April 1, 2026, 12:42 a.m.
Created at: March 30, 2026, 5:29 p.m.