Triple

T24826265
Position Surface form Disambiguated ID Type / Status
Subject North Haven Campus E621198 entity
Predicate affiliatedWith P254 FINISHED
Object Quinnipiac University School of Law
Quinnipiac University School of Law is a private law school in Connecticut offering J.D. and related legal programs as part of Quinnipiac University.
E1655483 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: Quinnipiac University School of Law | Statement: [North Haven Campus, affiliatedWith, Quinnipiac University School of Law]
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: Quinnipiac University School of Law
Triple: [North Haven Campus, affiliatedWith, Quinnipiac University School of Law]
Generated description
Quinnipiac University School of Law is a private law school in Connecticut offering J.D. and related legal programs as part of Quinnipiac University.

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_69e2fac0c3b881909110e5a56c6fa46f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4229cf6b08190a32887b534283d7d completed May 1, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1033118da4819094755a865c84d47e completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a1033be69f88190988f54e89df5438a completed May 22, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_6a10346cdcac8190865eb3c1b86c9c2c completed May 22, 2026, 10:48 a.m.
Created at: April 18, 2026, 5:05 a.m.