Triple

T34747842
Position Surface form Disambiguated ID Type / Status
Subject Walter de Burgh, 1st Earl of Ulster E1001685 entity
Predicate child P120 FINISHED
Object Egidia de Burgh
Egidia de Burgh was a 13th-century Anglo-Norman noblewoman of the powerful de Burgh family of Ireland, noted for her dynastic connections to the Earldom of Ulster.
E2114155 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: Egidia de Burgh | Statement: [Walter de Burgh, 1st Earl of Ulster, child, Egidia de Burgh]
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: Egidia de Burgh
Triple: [Walter de Burgh, 1st Earl of Ulster, child, Egidia de Burgh]
Generated description
Egidia de Burgh was a 13th-century Anglo-Norman noblewoman of the powerful de Burgh family of Ireland, noted for her dynastic connections to the Earldom of Ulster.

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_69f76db0367081909b57c50a7fb03025 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779e741e08190a35c38c81b5edcd7 completed May 3, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a376f9ad75c8190be10f170615d8856 completed June 21, 2026, 4:59 a.m.
NEDg Description generation batch_6a37707f2b448190b295001f220c8820 completed June 21, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_6a37714f04988190a982d73fee3272d3 completed June 21, 2026, 5:06 a.m.
Created at: May 3, 2026, 3:59 p.m.