Triple

T26298622
Position Surface form Disambiguated ID Type / Status
Subject Jeff Mayweather E661486 entity
Predicate trained P3665 FINISHED
Object Celestino Caballero
Celestino Caballero is a Panamanian former professional boxer and two-division world champion known for his height, reach, and success in the super bantamweight and featherweight divisions.
E1829647 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: Celestino Caballero | Statement: [Jeff Mayweather, trained, Celestino Caballero]
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: Celestino Caballero
Triple: [Jeff Mayweather, trained, Celestino Caballero]
Generated description
Celestino Caballero is a Panamanian former professional boxer and two-division world champion known for his height, reach, and success in the super bantamweight and featherweight divisions.

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_69ee812cd48c81908054068f545f0526 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60eb080b08190a45b05aa6d6219e9 completed May 2, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf08ca6081909f7294dc073f7136 completed June 1, 2026, 12:15 a.m.
NEDg Description generation batch_6a1ccff86fc88190b1438e77f3a5f101 completed June 1, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a24945efab88190a4ccb8a92331e469 completed June 6, 2026, 9:42 p.m.
Created at: April 26, 2026, 10:14 p.m.