Triple

T38041468
Position Surface form Disambiguated ID Type / Status
Subject Concordia University Chicago E949491 entity
Predicate formerName P65 FINISHED
Object Concordia Teachers College
Concordia Teachers College was a Lutheran-affiliated teacher education institution that later evolved into Concordia University Chicago.
E2256307 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: Concordia Teachers College | Statement: [Concordia University Chicago, formerName, Concordia Teachers College]
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: Concordia Teachers College
Triple: [Concordia University Chicago, formerName, Concordia Teachers College]
Generated description
Concordia Teachers College was a Lutheran-affiliated teacher education institution that later evolved into Concordia University Chicago.

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_69f76eff0bb0819084bc4e63997bd039 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc9d5abe88190ba3847bea26924ca completed May 6, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41680011a8819096a45e5afd7aef2f completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a41686a4b208190b66dafbfd517866c completed June 28, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_6a416a8db6508190b5dbdbb43f8c2685 completed June 28, 2026, 6:40 p.m.
Created at: May 3, 2026, 4:20 p.m.