Triple

T35704415
Position Surface form Disambiguated ID Type / Status
Subject Hearst College E1031676 entity
Predicate hasFacultyOrStaffCharacter P141 FINISHED
Object Dean’s wife Mindy O’Dell
Mindy O’Dell is a recurring character on the TV series "Veronica Mars," known as the wife of Hearst College’s dean and a central figure in one of the show’s major mystery arcs.
E2151345 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: Dean’s wife Mindy O’Dell | Statement: [Hearst College, hasFacultyOrStaffCharacter, Dean’s wife Mindy O’Dell]
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: Dean’s wife Mindy O’Dell
Triple: [Hearst College, hasFacultyOrStaffCharacter, Dean’s wife Mindy O’Dell]
Generated description
Mindy O’Dell is a recurring character on the TV series "Veronica Mars," known as the wife of Hearst College’s dean and a central figure in one of the show’s major mystery arcs.

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_69f76e0d393c8190b6303c64408736db completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fe0931f28481908c1d691efbb6fba5 completed May 8, 2026, 4:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38729c21908190ae5baf815c523aeb completed June 21, 2026, 11:24 p.m.
NEDg Description generation batch_6a3873b54e98819081d03d29202e0cce completed June 21, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_6a387471166481908564c7a5aa5fc646 completed June 21, 2026, 11:32 p.m.
Created at: May 3, 2026, 4:05 p.m.