Triple

T19165065
Position Surface form Disambiguated ID Type / Status
Subject Michael Zaslow E469157 entity
Predicate familyName P18 FINISHED
Object Zaslow
Zaslow is a surname most notably associated with American actor Michael Zaslow, known for his roles in daytime television soap operas.
 E1360943 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: Zaslow | Statement: [Michael Zaslow, familyName, Zaslow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zaslow
Context triple: [Michael Zaslow, familyName, Zaslow]
  • A. Zaslofsky
    Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
  • B. Zaleski
    Zaleski is a Polish surname most notably borne by August Zaleski, a prominent Polish diplomat and statesman who served as President of Poland in exile.
  • C. Zorinsky
    Zorinsky is a surname most notably associated with Edward Zorinsky, a U.S. senator from Nebraska in the late 20th century.
  • D. Zas
    Zas is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its rural landscapes and traditional Galician culture.
  • E. Zas
    Zas is the highest mountain on the Greek island of Naxos in the Cyclades, known for its prominent peak and hiking trails.
  • 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: Zaslow
Triple: [Michael Zaslow, familyName, Zaslow]
Generated description
Zaslow is a surname most notably associated with American actor Michael Zaslow, known for his roles in daytime television soap operas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zaslow
Target entity description: Zaslow is a surname most notably associated with American actor Michael Zaslow, known for his roles in daytime television soap operas.
  • A. Zaslofsky
    Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
  • B. Zaleski
    Zaleski is a Polish surname most notably borne by August Zaleski, a prominent Polish diplomat and statesman who served as President of Poland in exile.
  • C. Zorinsky
    Zorinsky is a surname most notably associated with Edward Zorinsky, a U.S. senator from Nebraska in the late 20th century.
  • D. Zas
    Zas is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its rural landscapes and traditional Galician culture.
  • E. Zas
    Zas is the highest mountain on the Greek island of Naxos in the Cyclades, known for its prominent peak and hiking trails.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f15e2720819084b1707497db26a2 completed April 20, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a06f25ef2208190842d2b29bee2c8ce completed May 15, 2026, 10:15 a.m.
NEDg Description generation batch_6a06f3864b848190bcc76953e1a261f3 completed May 15, 2026, 10:20 a.m.
NED2 Entity disambiguation (via description) batch_6a06f41c7c508190bf54e751ea0dfb7a completed May 15, 2026, 10:23 a.m.
Created at: April 10, 2026, 12:06 p.m.