Triple

T32365950
Position Surface form Disambiguated ID Type / Status
Subject Carnesecca Arena E826990 entity
Predicate formerName P65 FINISHED
Object Alumni Hall
Alumni Hall is the former name of Carnesecca Arena, an indoor sports venue on the campus of St. John’s University in Queens, New York.
 E2015784 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: Alumni Hall | Statement: [Carnesecca Arena, formerName, Alumni Hall]
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: Alumni Hall
Triple: [Carnesecca Arena, formerName, Alumni Hall]
Generated description
Alumni Hall is the former name of Carnesecca Arena, an indoor sports venue on the campus of St. John’s University in Queens, New York.

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_69f349166d548190887b412fe908e2f4 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6be9db42c819094f2f94d10dfd3e4 completed May 3, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3492859fcc819099b5a3084d809992 completed June 19, 2026, 12:51 a.m.
NEDg Description generation batch_6a3492f623908190b8c2de8b46b51b10 completed June 19, 2026, 12:53 a.m.
NED2 Entity disambiguation (via description) batch_6a34936278088190a18f59f308702af2 completed June 19, 2026, 12:54 a.m.
Created at: May 1, 2026, 12:50 a.m.