Triple

T9279292
Position Surface form Disambiguated ID Type / Status
Subject Pam Beesly E223028 entity
Predicate hasChild P369 FINISHED
Object Philip Halpert
Philip Halpert is the infant son of Jim Halpert and Pam Beesly on the U.S. television series "The Office."
E788051 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: Philip Halpert | Statement: [Pam Beesly, hasChild, Philip Halpert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philip Halpert
Context triple: [Pam Beesly, hasChild, Philip Halpert]
  • A. Pete Garvey
    Pete Garvey is the charming, fast-talking bachelor portrayed by Bing Crosby in the 1951 musical comedy film "Here Comes the Groom."
  • B. Felix Unger
    Felix Unger is an Austrian cardiac surgeon and academic known for co-founding and leading the European Academy of Sciences and Arts.
  • C. Felix Unger
    Felix Unger is a fictional, fastidious and neurotic neat-freak character best known as one of the mismatched roommates in Neil Simon’s play and subsequent adaptations of "The Odd Couple."
  • D. Jerry Mulligan
    Jerry Mulligan is the charismatic American ex-GI and aspiring painter living in postwar Paris who serves as the romantic lead in the musical film "An American in Paris."
  • E. Nathaniel Blume
    Nathaniel Blume is a contemporary American composer best known for his work on television and film scores, particularly in the crime and thriller genres.
  • 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: Philip Halpert
Triple: [Pam Beesly, hasChild, Philip Halpert]
Generated description
Philip Halpert is the infant son of Jim Halpert and Pam Beesly on the U.S. television series "The Office."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Philip Halpert
Target entity description: Philip Halpert is the infant son of Jim Halpert and Pam Beesly on the U.S. television series "The Office."
  • A. Pete Garvey
    Pete Garvey is the charming, fast-talking bachelor portrayed by Bing Crosby in the 1951 musical comedy film "Here Comes the Groom."
  • B. Felix Unger
    Felix Unger is an Austrian cardiac surgeon and academic known for co-founding and leading the European Academy of Sciences and Arts.
  • C. Felix Unger
    Felix Unger is a fictional, fastidious and neurotic neat-freak character best known as one of the mismatched roommates in Neil Simon’s play and subsequent adaptations of "The Odd Couple."
  • D. Jerry Mulligan
    Jerry Mulligan is the charismatic American ex-GI and aspiring painter living in postwar Paris who serves as the romantic lead in the musical film "An American in Paris."
  • E. Nathaniel Blume
    Nathaniel Blume is a contemporary American composer best known for his work on television and film scores, particularly in the crime and thriller genres.
  • 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_69ca842123588190b3f2e1a69037d141 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd07cc79508190954defbef0d82a64 completed April 1, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09c4f254c819083301449c3e4b11d completed April 4, 2026, 5:06 a.m.
NEDg Description generation batch_69d09da280288190b40f145e1836a53f completed April 4, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d09df7c7f48190b36b63227ff539b5 completed April 4, 2026, 5:13 a.m.
Created at: March 30, 2026, 7:34 p.m.