Triple

T28541039
Position Surface form Disambiguated ID Type / Status
Subject Around the Horn E722290 entity
Predicate hasHost P2592 FINISHED
Object Tony Reali
Tony Reali is an American sports television personality best known as the longtime host of ESPN’s debate show "Around the Horn."
E2047258 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: Tony Reali | Statement: [Around the Horn, hasHost, Tony Reali]
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: Tony Reali
Triple: [Around the Horn, hasHost, Tony Reali]
Generated description
Tony Reali is an American sports television personality best known as the longtime host of ESPN’s debate show "Around the Horn."

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_69f01a5e42348190b1ffbca26e739c84 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f650096f8c8190a3b528b3ca9b6e17 completed May 2, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3551d887f48190b718e6dabd16a1e8 completed June 19, 2026, 2:27 p.m.
NEDg Description generation batch_6a3553aeebc081909d55bb8589c5d40b completed June 19, 2026, 2:35 p.m.
NED2 Entity disambiguation (via description) batch_6a35555f59a481909f18895e896f5a1c completed June 19, 2026, 2:42 p.m.
Created at: April 28, 2026, 3:35 a.m.