Triple

T33278632
Position Surface form Disambiguated ID Type / Status
Subject Eastern Illinois Panthers football E851974 entity
Predicate hasNotableAlumnus P51 FINISHED
Object Chris Watson
Chris Watson is a former American football player and return specialist who played in the National Football League after starring at Eastern Illinois University.
E2043279 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: Chris Watson | Statement: [Eastern Illinois Panthers football, hasNotableAlumnus, Chris Watson]
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: Chris Watson
Triple: [Eastern Illinois Panthers football, hasNotableAlumnus, Chris Watson]
Generated description
Chris Watson is a former American football player and return specialist who played in the National Football League after starring at Eastern Illinois University.

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_69f349653da08190819876015a298fdb completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6de59e6648190b2fc3eb5c4bc9f98 completed May 3, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a353923c90081909b19f01125180e8e completed June 19, 2026, 12:42 p.m.
NEDg Description generation batch_6a3539c022308190bd3f226e23e46c84 completed June 19, 2026, 12:44 p.m.
NED2 Entity disambiguation (via description) batch_6a353a6dab4881909783ce7342655773 completed June 19, 2026, 12:47 p.m.
Created at: May 1, 2026, 1:32 a.m.