Triple

T36235636
Position Surface form Disambiguated ID Type / Status
Subject Nick Ross E891369 entity
Predicate category P87 FINISHED
Object English Football League players
English Football League players are professional footballers who have competed in league competitions organized by the English Football League in England.
E12541 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: English Football League players | Statement: [Nick Ross, category, English Football League players]
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: English Football League players
Triple: [Nick Ross, category, English Football League players]
Generated description
English Football League players are professional footballers who have competed in league competitions organized by the English Football League in England.

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_69f76e4387048190a1b27bcbf4ec7423 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b5a656808190b77b60d4703d0d91 completed May 3, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d3deb0c819090d0155a6647f47b completed June 22, 2026, 2:57 p.m.
NEDg Description generation batch_6a394f7a4dd481909ac14a8ba31d899b completed June 22, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_6a3954064be08190ab1cd122c2a53311 completed June 22, 2026, 3:25 p.m.
Created at: May 3, 2026, 4:09 p.m.