Triple

T35879302
Position Surface form Disambiguated ID Type / Status
Subject Marion, South Carolina E1037462 entity
Predicate hasHistoricBuilding P1098 FINISHED
Object Old Marion High School
Old Marion High School is a historic former educational building in Marion, South Carolina, recognized for its architectural and community significance.
E2159934 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: Old Marion High School | Statement: [Marion, South Carolina, hasHistoricBuilding, Old Marion High School]
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: Old Marion High School
Triple: [Marion, South Carolina, hasHistoricBuilding, Old Marion High School]
Generated description
Old Marion High School is a historic former educational building in Marion, South Carolina, recognized for its architectural and community significance.

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_69f76e1e701c8190a4990d4978ce4fe6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa048124819083a93f758b2f115e completed May 3, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4f4cff48190800057f11b9d46b9 completed June 22, 2026, 2:59 a.m.
NEDg Description generation batch_6a38a64c9f408190962c13d1c40a5988 completed June 22, 2026, 3:04 a.m.
NED2 Entity disambiguation (via description) batch_6a38a6e814588190a5f439f44470ef26 completed June 22, 2026, 3:07 a.m.
Created at: May 3, 2026, 4:06 p.m.