Triple

T23594817
Position Surface form Disambiguated ID Type / Status
Subject Jerry Springer E582584 entity
Predicate fullName P16 FINISHED
Object Gerald Norman Springer
Gerald Norman Springer was a British-born American television presenter, former politician, and longtime host of the sensational tabloid talk show "The Jerry Springer Show."
E1607359 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: Gerald Norman Springer | Statement: [Jerry Springer, fullName, Gerald Norman Springer]
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: Gerald Norman Springer
Triple: [Jerry Springer, fullName, Gerald Norman Springer]
Generated description
Gerald Norman Springer was a British-born American television presenter, former politician, and longtime host of the sensational tabloid talk show "The Jerry Springer Show."

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_69e248f9e0a08190814772847003b1ff completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b08e9aa4819091099dfc2074b22d completed April 29, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75f3df5c819084519fc96c6813f1 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f76cc78748190b0f22716094bba19 completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77541b948190bb866a8c7c6f5ca9 completed May 21, 2026, 9:21 p.m.
Created at: April 17, 2026, 6:42 p.m.