Triple

T32720779
Position Surface form Disambiguated ID Type / Status
Subject Herb Stempel E836667 entity
Predicate birthName P65 FINISHED
Object Herbert Milton Stempel
Herbert Milton Stempel was an American quiz show contestant best known for exposing the rigging of the 1950s television game show "Twenty-One," helping to trigger a major scandal and reforms in broadcast standards.
E2020661 NE FINISHED

How this triple was built (2 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: Herbert Milton Stempel | Statement: [Herb Stempel, birthName, Herbert Milton Stempel]
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: Herbert Milton Stempel
Triple: [Herb Stempel, birthName, Herbert Milton Stempel]
Generated description
Herbert Milton Stempel was an American quiz show contestant best known for exposing the rigging of the 1950s television game show "Twenty-One," helping to trigger a major scandal and reforms in broadcast standards.

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_69f34935455881909088975d79460418 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c8b304ec8190b63babe3982c0b68 completed May 3, 2026, 4:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34a7a68808819090492253a6c3f50b completed June 19, 2026, 2:21 a.m.
NEDg Description generation batch_6a34a833f2508190809ee7c42e2da9d3 completed June 19, 2026, 2:23 a.m.
NED2 Entity disambiguation (via description) batch_6a34a8dde9f48190b9912c18f2470edf completed June 19, 2026, 2:26 a.m.
Created at: May 1, 2026, 1:11 a.m.