Triple

T4928493
Position Surface form Disambiguated ID Type / Status
Subject Frank Lautenberg E110633 entity
Predicate succeededBy P78 FINISHED
Object Jeff Chiesa
Jeff Chiesa is an American attorney and Republican politician who briefly served as a U.S. Senator from New Jersey after being appointed to fill a vacancy.
E480317 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: Jeff Chiesa | Statement: [Frank Lautenberg, succeededBy, Jeff Chiesa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeff Chiesa
Context triple: [Frank Lautenberg, succeededBy, Jeff Chiesa]
  • A. Luke Daboll
    Luke Daboll is a member of the Daboll family, known primarily as a relative of NFL head coach Brian Daboll.
  • B. Christian Daboll
    Christian Daboll is a member of the Daboll family, related to NFL head coach Brian Daboll.
  • C. Matt Eberflus
    Matt Eberflus is an American football coach and former NFL defensive coordinator who serves as the head coach of the Chicago Bears.
  • D. Matt Birk
    Matt Birk is a former NFL center, primarily for the Minnesota Vikings and Baltimore Ravens, who became a Super Bowl champion and later an executive with the league.
  • E. Ryan Ruocco
    Ryan Ruocco is an American sportscaster best known for his play-by-play work on New York Yankees and Brooklyn Nets broadcasts and for calling WNBA games on national television.
  • 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: Jeff Chiesa
Triple: [Frank Lautenberg, succeededBy, Jeff Chiesa]
Generated description
Jeff Chiesa is an American attorney and Republican politician who briefly served as a U.S. Senator from New Jersey after being appointed to fill a vacancy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jeff Chiesa
Target entity description: Jeff Chiesa is an American attorney and Republican politician who briefly served as a U.S. Senator from New Jersey after being appointed to fill a vacancy.
  • A. Luke Daboll
    Luke Daboll is a member of the Daboll family, known primarily as a relative of NFL head coach Brian Daboll.
  • B. Christian Daboll
    Christian Daboll is a member of the Daboll family, related to NFL head coach Brian Daboll.
  • C. Matt Eberflus
    Matt Eberflus is an American football coach and former NFL defensive coordinator who serves as the head coach of the Chicago Bears.
  • D. Matt Birk
    Matt Birk is a former NFL center, primarily for the Minnesota Vikings and Baltimore Ravens, who became a Super Bowl champion and later an executive with the league.
  • E. Ryan Ruocco
    Ryan Ruocco is an American sportscaster best known for his play-by-play work on New York Yankees and Brooklyn Nets broadcasts and for calling WNBA games on national television.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7038c12c81908a793b4a8768c28a completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77af13308190b99f3aca0cb44c61 completed March 21, 2026, 10:49 a.m.
NEDg Description generation batch_69be781aa8648190a58587e6f3e04e11 completed March 21, 2026, 10:51 a.m.
NED2 Entity disambiguation (via description) batch_69be78a0bdc88190bd8458658f15f879 completed March 21, 2026, 10:53 a.m.
Created at: March 20, 2026, 1:30 p.m.