Triple

T35000423
Position Surface form Disambiguated ID Type / Status
Subject Reverend Winemiller E1009658 entity
Predicate fictionalLocation P18263 FINISHED
Object Glorious Hill, Mississippi
Glorious Hill, Mississippi is the small Southern town that serves as the primary setting for Tennessee Williams’ play "Summer and Smoke."
E2120788 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: Glorious Hill, Mississippi | Statement: [Reverend Winemiller, fictionalLocation, Glorious Hill, Mississippi]
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: Glorious Hill, Mississippi
Triple: [Reverend Winemiller, fictionalLocation, Glorious Hill, Mississippi]
Generated description
Glorious Hill, Mississippi is the small Southern town that serves as the primary setting for Tennessee Williams’ play "Summer and Smoke."

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_69f76dcb716881909f75e4fd60ab2284 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f784e614ec8190986e7fcd0c1fc7fd completed May 3, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b292134481908154ae4bb096c012 completed June 21, 2026, 9:44 a.m.
NEDg Description generation batch_6a37b37283f48190ac9d30605260de2f completed June 21, 2026, 9:48 a.m.
NED2 Entity disambiguation (via description) batch_6a37b5345c088190b28e008ba62610da completed June 21, 2026, 9:56 a.m.
Created at: May 3, 2026, 4:01 p.m.