Triple

T23486907
Position Surface form Disambiguated ID Type / Status
Subject Florence Jean "Flo" Castleberry E570557 entity
Predicate setting P1957 FINISHED
Object Cowtown, Texas
Cowtown, Texas is the fictional small Texas town that serves as the hometown backdrop for the character Florence Jean "Flo" Castleberry in the TV series "Flo."
E1630091 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: Cowtown, Texas | Statement: [Florence Jean "Flo" Castleberry, setting, Cowtown, Texas]
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: Cowtown, Texas
Triple: [Florence Jean "Flo" Castleberry, setting, Cowtown, Texas]
Generated description
Cowtown, Texas is the fictional small Texas town that serves as the hometown backdrop for the character Florence Jean "Flo" Castleberry in the TV series "Flo."

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_69e245b0b01481908f636939bedd804c completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a754825481909b005ca5654c3159 completed April 29, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc989a41c8190b10d74bf87c8478c completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcd8c82748190b9eac125ba8f08f3 completed May 22, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd1a9df748190b9d4af9fec6a9f78 completed May 22, 2026, 3:46 a.m.
Created at: April 17, 2026, 6:04 p.m.