Triple

T28556829
Position Surface form Disambiguated ID Type / Status
Subject Legion of Boom defense era E723029 entity
Predicate keyPlayer P44793 FINISHED
Object Walter Thurmond
Walter Thurmond is a former NFL cornerback best known for his role in the Seattle Seahawks’ dominant secondary during their Super Bowl-winning years.
E1823952 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: Walter Thurmond | Statement: [Legion of Boom defense era, keyPlayer, Walter Thurmond]
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: Walter Thurmond
Triple: [Legion of Boom defense era, keyPlayer, Walter Thurmond]
Generated description
Walter Thurmond is a former NFL cornerback best known for his role in the Seattle Seahawks’ dominant secondary during their Super Bowl-winning years.

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_69f01a60204481909af1bb76247b8221 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f6505097348190b46266efd9cd007d completed May 2, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6e4a004819091d6dfc944fc9e5c completed May 31, 2026, 10:32 p.m.
NEDg Description generation batch_6a1cb79e7c588190a3e027d81075cc8a completed May 31, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_6a1cb7fe39ac8190afad2681deae4e36 completed May 31, 2026, 10:36 p.m.
Created at: April 28, 2026, 3:46 a.m.