Triple

T35623623
Position Surface form Disambiguated ID Type / Status
Subject Hal March E1029385 entity
Predicate birthName P65 FINISHED
Object Harold Mendelson
Harold Mendelson, better known by his stage name Hal March, was an American comedian and actor most famous for hosting the 1950s television game show "The $64,000 Question."
E2287192 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: Harold Mendelson | Statement: [Hal March, birthName, Harold Mendelson]
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: Harold Mendelson
Triple: [Hal March, birthName, Harold Mendelson]
Generated description
Harold Mendelson, better known by his stage name Hal March, was an American comedian and actor most famous for hosting the 1950s television game show "The $64,000 Question."

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_69f76e0709408190bbe322bf1707ef6b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79ef3d120819084fb33df17a73b15 completed May 3, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4767e2697481908712d82281a4a404 completed July 3, 2026, 7:42 a.m.
NEDg Description generation batch_6a476a4eb364819099e257a3b6bdb518 completed July 3, 2026, 7:52 a.m.
NED2 Entity disambiguation (via description) batch_6a476aaf619c81908c438b025fc4e3a1 completed July 3, 2026, 7:54 a.m.
Created at: May 3, 2026, 4:05 p.m.