Triple

T27597533
Position Surface form Disambiguated ID Type / Status
Subject Watts College of Public Service and Community Solutions E699941 entity
Predicate namedAfter P63 FINISHED
Object Cindy Watts
Cindy Watts is the namesake of Arizona State University’s Watts College of Public Service and Community Solutions, recognized for her significant philanthropic and community-focused contributions.
E1842274 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: Cindy Watts | Statement: [Watts College of Public Service and Community Solutions, namedAfter, Cindy Watts]
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: Cindy Watts
Triple: [Watts College of Public Service and Community Solutions, namedAfter, Cindy Watts]
Generated description
Cindy Watts is the namesake of Arizona State University’s Watts College of Public Service and Community Solutions, recognized for her significant philanthropic and community-focused contributions.

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_69ef6a4d71f081909a1235763206b691 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f63059a9688190a93035f948c02a07 completed May 2, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec14e6388190ba6b15741ad914b8 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f07e3a54819090dc0d92cee92204 completed June 7, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a24f56a17a48190a309ea59a2ebf4d1 completed June 7, 2026, 4:36 a.m.
Created at: April 27, 2026, 2:07 p.m.