Triple

T37028560
Position Surface form Disambiguated ID Type / Status
Subject Stanley Carter E916423 entity
Predicate kills P19780 FINISHED
Object Reverend Jackson T. Tolliver
Reverend Jackson T. Tolliver is a fictional clergyman character known primarily as the murder victim of Stanley Carter in his narrative context.
E2209297 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: Reverend Jackson T. Tolliver | Statement: [Stanley Carter, kills, Reverend Jackson T. Tolliver]
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: Reverend Jackson T. Tolliver
Triple: [Stanley Carter, kills, Reverend Jackson T. Tolliver]
Generated description
Reverend Jackson T. Tolliver is a fictional clergyman character known primarily as the murder victim of Stanley Carter in his narrative context.

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_69f76e92c7648190bcfa277f64c71a21 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fa00d7a76c8190a29972a785050b1a completed May 5, 2026, 2:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e577c302881909c8520f93ca83422 completed June 26, 2026, 10:42 a.m.
NEDg Description generation batch_6a3e582b14f48190965bd9f10b1b3f1a completed June 26, 2026, 10:44 a.m.
NED2 Entity disambiguation (via description) batch_6a3e82f3722481909ea787f30e07b8b0 completed June 26, 2026, 1:47 p.m.
Created at: May 3, 2026, 4:14 p.m.