Triple

T38076417
Position Surface form Disambiguated ID Type / Status
Subject Denver Gold E950723 entity
Predicate participatedIn P149 FINISHED
Object USFL regular season
The USFL regular season was the primary schedule of professional American football games played each year in the United States Football League before its postseason.
E2254114 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: USFL regular season | Statement: [Denver Gold, participatedIn, USFL regular season]
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: USFL regular season
Triple: [Denver Gold, participatedIn, USFL regular season]
Generated description
The USFL regular season was the primary schedule of professional American football games played each year in the United States Football League before its postseason.

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_69f76f02a6c48190a94f3c0b3ee90cf2 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbca6a8a188190a331f8f9730f2bcf completed May 6, 2026, 11:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a415d45f6f481909194675425133597 completed June 28, 2026, 5:43 p.m.
NEDg Description generation batch_6a415dcfde888190956fb3224e950f4e completed June 28, 2026, 5:45 p.m.
NED2 Entity disambiguation (via description) batch_6a415e51d2708190b648410e39c49c30 completed June 28, 2026, 5:48 p.m.
Created at: May 3, 2026, 4:21 p.m.