Triple

T20999973
Position Surface form Disambiguated ID Type / Status
Subject Fulk II of Anjou E517258 entity
Predicate spouse P13 FINISHED
Object Adelaide of Vermandois
Adelaide of Vermandois was a 10th-century French noblewoman from the influential Carolingian-linked Vermandois family who became Countess of Anjou through her marriage to Fulk II.
E1723560 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: Adelaide of Vermandois | Statement: [Fulk II of Anjou, spouse, Adelaide of Vermandois]
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: Adelaide of Vermandois
Triple: [Fulk II of Anjou, spouse, Adelaide of Vermandois]
Generated description
Adelaide of Vermandois was a 10th-century French noblewoman from the influential Carolingian-linked Vermandois family who became Countess of Anjou through her marriage to Fulk 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_69e0b5006e2881909fc2383f841740cc completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc24a6dc8190a6bf81cf1d9590c0 completed April 21, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a11ae81aa088190a09c47ab591cef61 completed May 23, 2026, 1:41 p.m.
NEDg Description generation batch_6a11af6832f08190ab2673c8502f0526 completed May 23, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a11b0097edc81909327051db358c7b1 completed May 23, 2026, 1:47 p.m.
Created at: April 16, 2026, 1:51 p.m.