Triple

T34240080
Position Surface form Disambiguated ID Type / Status
Subject The Visit (Broadway) E878437 entity
Predicate character P662 FINISHED
Object Anton Schell
Anton Schell is a central male character in the play "The Visit," whose past actions toward the protagonist, Claire Zachanassian, drive the story’s themes of justice, revenge, and moral corruption.
E2100904 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: Anton Schell | Statement: [The Visit (Broadway), character, Anton Schell]
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: Anton Schell
Triple: [The Visit (Broadway), character, Anton Schell]
Generated description
Anton Schell is a central male character in the play "The Visit," whose past actions toward the protagonist, Claire Zachanassian, drive the story’s themes of justice, revenge, and moral corruption.

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_69f349b22d8c819096b22df268382aa9 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7127d3e30819094f2a86ca45ae307 completed May 3, 2026, 9:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3729c48d808190b039baec6ad27c3e completed June 21, 2026, 12:01 a.m.
NEDg Description generation batch_6a372a638d8c8190bac677307e904fee completed June 21, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a372aba50cc819085899305ab23f1df completed June 21, 2026, 12:05 a.m.
Created at: May 1, 2026, 1:56 a.m.