Triple

T36564073
Position Surface form Disambiguated ID Type / Status
Subject Embleton E901923 entity
Predicate hasLandmark P105 FINISHED
Object Parish church of Holy Trinity
The Parish Church of Holy Trinity is a historic Anglican church serving as a prominent religious and architectural landmark in the village of Embleton, England.
E2188715 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: Parish church of Holy Trinity | Statement: [Embleton, hasLandmark, Parish church of Holy Trinity]
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: Parish church of Holy Trinity
Triple: [Embleton, hasLandmark, Parish church of Holy Trinity]
Generated description
The Parish Church of Holy Trinity is a historic Anglican church serving as a prominent religious and architectural landmark in the village of Embleton, England.

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_69f76e6416708190a9754b8c52d4e453 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c27e8b388190ac58d84ca5edadac completed May 3, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6f656f481908ba8357ffb65102e completed June 23, 2026, 1:52 a.m.
NEDg Description generation batch_6a39e7943be881909c7ed1ce33ad96d8 completed June 23, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_6a39ea9c403c8190a44d9289b4fee998 completed June 23, 2026, 2:08 a.m.
Created at: May 3, 2026, 4:11 p.m.