Triple

T25017391
Position Surface form Disambiguated ID Type / Status
Subject Vladislaus II, King of Bohemia E626176 entity
Predicate spouse P13 FINISHED
Object Gertrude of Babenberg
Gertrude of Babenberg was a 12th-century Austrian noblewoman from the influential Babenberg dynasty who became Queen consort of Bohemia through her marriage to Vladislaus II.
E1678192 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: Gertrude of Babenberg | Statement: [Vladislaus II, King of Bohemia, spouse, Gertrude of Babenberg]
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: Gertrude of Babenberg
Triple: [Vladislaus II, King of Bohemia, spouse, Gertrude of Babenberg]
Generated description
Gertrude of Babenberg was a 12th-century Austrian noblewoman from the influential Babenberg dynasty who became Queen consort of Bohemia through her marriage to Vladislaus II.

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_69e2ff27755881908490178e83701160 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44ba720748190a16124b842247df2 completed May 1, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10895d55388190a760f26b4caf2a1d completed May 22, 2026, 4:50 p.m.
NEDg Description generation batch_6a108a0af25481909d520360b86ff170 completed May 22, 2026, 4:53 p.m.
NED2 Entity disambiguation (via description) batch_6a108afb4ad08190a1e9bcd731d98fcb completed May 22, 2026, 4:57 p.m.
Created at: April 18, 2026, 6:06 a.m.