Triple

T3461900
Position Surface form Disambiguated ID Type / Status
Subject Oscar Hammerstein I E73043 entity
Predicate givenName P17 FINISHED
Object Oscar
Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
 E359307 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: Oscar | Statement: [Oscar Hammerstein I, givenName, Oscar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oscar
Context triple: [Oscar Hammerstein I, givenName, Oscar]
  • A. Oscar
    The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
  • B. Oscar
    Oscar is the Allied reporting name for the Nakajima Ki-43, a Japanese World War II fighter aircraft used extensively by the Imperial Japanese Army Air Service.
  • C. OSCAR
    OSCAR is the proprietary messaging protocol developed by AOL to power its real-time chat and presence services across products like AIM and ICQ.
  • D. Orson
    Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
  • E. Emmy
    Emmy is the iconic winged woman holding an atom statuette that serves as the symbol and trophy for the Primetime Emmy Awards.
  • 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: Oscar
Triple: [Oscar Hammerstein I, givenName, Oscar]
Generated description
Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oscar
Target entity description: Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
  • A. Oscar
    The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
  • B. Oscar
    Oscar is the Allied reporting name for the Nakajima Ki-43, a Japanese World War II fighter aircraft used extensively by the Imperial Japanese Army Air Service.
  • C. OSCAR
    OSCAR is the proprietary messaging protocol developed by AOL to power its real-time chat and presence services across products like AIM and ICQ.
  • D. Orson
    Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
  • E. Emmy
    Emmy is the affectionate nickname of Emmy Noether, the pioneering German mathematician renowned for her groundbreaking contributions to abstract algebra and theoretical physics.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbae867c4819091c76e63e44290b4 completed March 8, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3611ff950819081b49f5c75aa6e4d completed March 13, 2026, 12:58 a.m.
NEDg Description generation batch_69b3629f2e54819091b38de147996782 completed March 13, 2026, 1:04 a.m.
NED2 Entity disambiguation (via description) batch_69b3630f5628819080ab239790cf4f4d completed March 13, 2026, 1:06 a.m.
Created at: March 8, 2026, 3:17 p.m.