Triple

T16197810
Position Surface form Disambiguated ID Type / Status
Subject Boston Public E393112 entity
Predicate mainCharacter P1183 FINISHED
Object Lipschultz
Lipschultz is a recurring teacher character on the television drama "Boston Public," known for his old-fashioned views and frequent clashes with students and staff.
 E1198776 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: Lipschultz | Statement: [Boston Public, mainCharacter, Lipschultz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lipschultz
Context triple: [Boston Public, mainCharacter, Lipschultz]
  • A. Lipsitz
    Lipsitz is a variant spelling of the Jewish surname Lifshitz, which has Ashkenazi origins.
  • B. Levshitz
    Levshitz is an alternative transliteration of the Russian surname Lifshitz, commonly associated with several notable scientists and intellectuals.
  • C. Zaslofsky
    Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
  • D. Schultheiss
    Schultheiss is a German surname historically derived from a medieval administrative title for a local official or magistrate.
  • E. Wilutzky
    Wilutzky is a German surname most notably borne by film producer and director Dirk Wilutzky.
  • 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: Lipschultz
Triple: [Boston Public, mainCharacter, Lipschultz]
Generated description
Lipschultz is a recurring teacher character on the television drama "Boston Public," known for his old-fashioned views and frequent clashes with students and staff.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lipschultz
Target entity description: Lipschultz is a recurring teacher character on the television drama "Boston Public," known for his old-fashioned views and frequent clashes with students and staff.
  • A. Lipsitz
    Lipsitz is a variant spelling of the Jewish surname Lifshitz, which has Ashkenazi origins.
  • B. Levshitz
    Levshitz is an alternative transliteration of the Russian surname Lifshitz, commonly associated with several notable scientists and intellectuals.
  • C. Zaslofsky
    Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
  • D. Schultheiss
    Schultheiss is a German surname historically derived from a medieval administrative title for a local official or magistrate.
  • E. Wilutzky
    Wilutzky is a German surname most notably borne by film producer and director Dirk Wilutzky.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222dc6b1c8190a3d8a6451ed8b95a completed April 17, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffff0f352081908324783743e47029 completed May 10, 2026, 3:44 a.m.
NEDg Description generation batch_6a00003d347481908285b2253fd20ac1 completed May 10, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_6a0000adc1b08190abbafcabb4ebc079 completed May 10, 2026, 3:51 a.m.
Created at: April 10, 2026, 5:02 a.m.