Triple

T31657100
Position Surface form Disambiguated ID Type / Status
Subject Cedar Crest College E807884 entity
Predicate motto P42 FINISHED
Object “Life in a Liberal Art”
“Life in a Liberal Art” is the official motto of Cedar Crest College, encapsulating its emphasis on a broad, humanistic liberal arts education.
 E1970556 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: “Life in a Liberal Art” | Statement: [Cedar Crest College, motto, “Life in a Liberal Art”]
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: “Life in a Liberal Art”
Triple: [Cedar Crest College, motto, “Life in a Liberal Art”]
Generated description
“Life in a Liberal Art” is the official motto of Cedar Crest College, encapsulating its emphasis on a broad, humanistic liberal arts education.

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_69f348daf95c81908b4c985b7ddcd0b3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a95f453081908414920057d97c90 completed May 3, 2026, 1:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79e926b08190a95beab4c930d24f completed June 12, 2026, 3:15 a.m.
NEDg Description generation batch_6a2b7a6983e481908c22bc6844ca0bd2 completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b739c488190b25323f8e490b2e4 completed June 12, 2026, 3:22 a.m.
Created at: April 30, 2026, 10:55 p.m.