Triple

T37724045
Position Surface form Disambiguated ID Type / Status
Subject 2012 BCS National Championship Game E939668 entity
Predicate MVP P2630 FINISHED
Object Eddie Lacy
Eddie Lacy is a former American football running back best known for his standout college career at Alabama and subsequent tenure with the Green Bay Packers in the NFL.
E2241392 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: Eddie Lacy | Statement: [2012 BCS National Championship Game, MVP, Eddie Lacy]
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: Eddie Lacy
Triple: [2012 BCS National Championship Game, MVP, Eddie Lacy]
Generated description
Eddie Lacy is a former American football running back best known for his standout college career at Alabama and subsequent tenure with the Green Bay Packers in the NFL.

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_69f76edc208c8190bc8b9683f75e1024 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbae74d67881909d1860c3a4c99602 completed May 6, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d67df1d8819090bf038521de2c5d completed June 28, 2026, 8:08 a.m.
NEDg Description generation batch_6a40da63f78081908dee41d23c8d4026 completed June 28, 2026, 8:25 a.m.
NED2 Entity disambiguation (via description) batch_6a40db0ab1c481909d3db018dd2b8bde completed June 28, 2026, 8:27 a.m.
Created at: May 3, 2026, 4:18 p.m.