Triple

T38008113
Position Surface form Disambiguated ID Type / Status
Subject Burning Man temples E948286 entity
Predicate templeNameExample P44027 FINISHED
Object Temple of Grace
Temple of Grace is a large, intricately designed spiritual structure that served as the central temple at the Burning Man festival, offering participants a space for reflection, mourning, and communal ritual.
E2252385 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: Temple of Grace | Statement: [Burning Man temples, templeNameExample, Temple of Grace]
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: Temple of Grace
Triple: [Burning Man temples, templeNameExample, Temple of Grace]
Generated description
Temple of Grace is a large, intricately designed spiritual structure that served as the central temple at the Burning Man festival, offering participants a space for reflection, mourning, and communal ritual.

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_69f76efb4b10819092c8c2ba28ac06a8 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc45674d288190b2fb29d898cc5f65 completed May 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a415433c9d4819098696f85a1125c87 completed June 28, 2026, 5:04 p.m.
NEDg Description generation batch_6a4154ac9b788190b6c6100d26bbfb4d completed June 28, 2026, 5:06 p.m.
NED2 Entity disambiguation (via description) batch_6a41552062048190916933791c8925e2 completed June 28, 2026, 5:08 p.m.
Created at: May 3, 2026, 4:20 p.m.