Triple

T38641697
Position Surface form Disambiguated ID Type / Status
Subject Red Dragons E938610 entity
Predicate rivalry P903 FINISHED
Object Cortaca Jug
The Cortaca Jug is a famed college football trophy contested annually between Ithaca College and SUNY Cortland, often dubbed the “biggest little game in the nation.”
E2279014 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: Cortaca Jug | Statement: [Red Dragons, rivalry, Cortaca Jug]
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: Cortaca Jug
Triple: [Red Dragons, rivalry, Cortaca Jug]
Generated description
The Cortaca Jug is a famed college football trophy contested annually between Ithaca College and SUNY Cortland, often dubbed the “biggest little game in the nation.”

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_69f76ed948ec81908ce7811608a8f359 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd9bd86f48190a6e295f3b6b0e76b completed May 7, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41f45af5a881908409ee5a08270460 completed June 29, 2026, 4:28 a.m.
NEDg Description generation batch_6a41f4fbde8c819096617301e3ece13c completed June 29, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a41f8d699bc8190a33eea34eff1e4d8 completed June 29, 2026, 4:47 a.m.
Created at: May 3, 2026, 4:32 p.m.