Triple

T27681527
Position Surface form Disambiguated ID Type / Status
Subject Merewalh E697920 entity
Predicate spouse P13 FINISHED
Object Saint Ermenburga
Saint Ermenburga was a 7th-century Anglo-Saxon royal woman and abbess, venerated as a Christian saint for her piety and role in founding religious communities in Kent.
E1786917 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: Saint Ermenburga | Statement: [Merewalh, spouse, Saint Ermenburga]
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: Saint Ermenburga
Triple: [Merewalh, spouse, Saint Ermenburga]
Generated description
Saint Ermenburga was a 7th-century Anglo-Saxon royal woman and abbess, venerated as a Christian saint for her piety and role in founding religious communities in Kent.

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_69ef590df8708190af5488f0638e790c completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f63538f2388190919cba716e850b5b completed May 2, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e450f824819089018c2d1a151199 completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e5c4d7388190b977f2268212f04f completed May 24, 2026, 11:49 a.m.
NED2 Entity disambiguation (via description) batch_6a12e658fe4c8190b4fbbbc2a8a4f796 completed May 24, 2026, 11:51 a.m.
Created at: April 27, 2026, 2:47 p.m.