Triple

T24452594
Position Surface form Disambiguated ID Type / Status
Subject American Gothic (TV series) E616587 entity
Predicate settingPlace P1957 FINISHED
Object Trinity, South Carolina
Trinity, South Carolina is a fictional small Southern town known as the eerie, supernatural setting of the television series "American Gothic."
E1675805 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: Trinity, South Carolina | Statement: [American Gothic (TV series), settingPlace, Trinity, South Carolina]
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: Trinity, South Carolina
Triple: [American Gothic (TV series), settingPlace, Trinity, South Carolina]
Generated description
Trinity, South Carolina is a fictional small Southern town known as the eerie, supernatural setting of the television series "American Gothic."

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_69e2d7edca608190aafefc8877a1b4da completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29859b824819087d4c7550dcbc426 completed April 29, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1075a3ad608190b15cd43f46bd6cd0 completed May 22, 2026, 3:26 p.m.
NEDg Description generation batch_6a1076b9b58881908eb0b619471c3879 completed May 22, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1077d01fa08190b5439eba879538ef completed May 22, 2026, 3:35 p.m.
Created at: April 18, 2026, 2:18 a.m.