Triple

T37400539
Position Surface form Disambiguated ID Type / Status
Subject Shattuck-St. Mary's E928981 entity
Predicate hasNotableAlumni P51 FINISHED
Object Rocco Grimaldi
Rocco Grimaldi is an American professional ice hockey forward known for his speed and scoring ability, who has played in the NHL and represented the United States in international competition.
E2225540 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: Rocco Grimaldi | Statement: [Shattuck-St. Mary's, hasNotableAlumni, Rocco Grimaldi]
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: Rocco Grimaldi
Triple: [Shattuck-St. Mary's, hasNotableAlumni, Rocco Grimaldi]
Generated description
Rocco Grimaldi is an American professional ice hockey forward known for his speed and scoring ability, who has played in the NHL and represented the United States in international competition.

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_69f76ebbf79c8190b85bbcf3a6be57e4 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8d5d520481908829ea4b938b624b completed May 6, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a407709e7d88190bba9d2bb29d1246e completed June 28, 2026, 1:21 a.m.
NEDg Description generation batch_6a407841ee948190b45372dab14ea45f completed June 28, 2026, 1:26 a.m.
NED2 Entity disambiguation (via description) batch_6a40791b81a481908283707caf3d7394 completed June 28, 2026, 1:30 a.m.
Created at: May 3, 2026, 4:16 p.m.