Triple

T27054098
Position Surface form Disambiguated ID Type / Status
Subject White Hall, Alabama E684852 entity
Predicate namedAfter P63 FINISHED
Object White Hall plantation
White Hall plantation was a historic Southern plantation whose name was later adopted by the town of White Hall, Alabama.
 E1755757 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: White Hall plantation | Statement: [White Hall, Alabama, namedAfter, White Hall plantation]
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: White Hall plantation
Triple: [White Hall, Alabama, namedAfter, White Hall plantation]
Generated description
White Hall plantation was a historic Southern plantation whose name was later adopted by the town of White Hall, Alabama.

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_69ef14829fac8190914bef9ecc3005d7 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f622b26848819098a558a4baf592fa completed May 2, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247f7dd1c819090d3d2d28cf401ce completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a12486c3d048190b11329247c3e8a01 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a1248effb2881909deeccdce34e3b0f completed May 24, 2026, 12:40 a.m.
Created at: April 27, 2026, 8:16 a.m.