Triple

T20645621
Position Surface form Disambiguated ID Type / Status
Subject The Station Agent E507346 entity
Predicate mainCharacter P1183 FINISHED
Object Joe Oramas
Joe Oramas is a friendly, talkative hot dog vendor who befriends the reclusive protagonist in the indie film "The Station Agent."
E1442580 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: Joe Oramas | Statement: [The Station Agent, mainCharacter, Joe Oramas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joe Oramas
Context triple: [The Station Agent, mainCharacter, Joe Oramas]
  • A. Joe Oros
    Joe Oros was an American automobile designer best known for leading the design team that created the original Ford Mustang.
  • B. Don Orsillo
    Don Orsillo is an American sportscaster best known as a longtime play-by-play announcer for Major League Baseball broadcasts, particularly for the Boston Red Sox and later the San Diego Padres.
  • C. Nick O'Brien
    Nick O'Brien is a hard-edged, morally ambiguous Los Angeles County Sheriff's detective who leads an elite unit in the crime thriller film "Den of Thieves."
  • D. Joe Corallo
    Joe Corallo is a comic book writer and editor known for his work on independent and genre titles in the modern comics scene.
  • E. Peter O’Neill
    Peter O’Neill is a Papua New Guinean politician who served as Prime Minister of Papua New Guinea from 2011 to 2019.
  • 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: Joe Oramas
Triple: [The Station Agent, mainCharacter, Joe Oramas]
Generated description
Joe Oramas is a friendly, talkative hot dog vendor who befriends the reclusive protagonist in the indie film "The Station Agent."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Joe Oramas
Target entity description: Joe Oramas is a friendly, talkative hot dog vendor who befriends the reclusive protagonist in the indie film "The Station Agent."
  • A. Joe Oros
    Joe Oros was an American automobile designer best known for leading the design team that created the original Ford Mustang.
  • B. Don Orsillo
    Don Orsillo is an American sportscaster best known as a longtime play-by-play announcer for Major League Baseball broadcasts, particularly for the Boston Red Sox and later the San Diego Padres.
  • C. Nick O'Brien
    Nick O'Brien is a hard-edged, morally ambiguous Los Angeles County Sheriff's detective who leads an elite unit in the crime thriller film "Den of Thieves."
  • D. Joe Corallo
    Joe Corallo is a comic book writer and editor known for his work on independent and genre titles in the modern comics scene.
  • E. Peter O’Neill
    Peter O’Neill is a Papua New Guinean politician who served as Prime Minister of Papua New Guinea from 2011 to 2019.
  • 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_69e0b4be702c8190a3d2410a881d310a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af1dd79481909de985d03ab861c2 completed April 20, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08c58e9b0081908fd2c4f3d8022401 completed May 16, 2026, 7:29 p.m.
NEDg Description generation batch_6a08c65993408190859c75fb65ade257 completed May 16, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_6a08c78fe4d48190a7a69f65f64ac66c completed May 16, 2026, 7:37 p.m.
Created at: April 16, 2026, 11:43 a.m.