Triple

T24696592
Position Surface form Disambiguated ID Type / Status
Subject William of Valence E611605 entity
Predicate titleThroughMarriage P21956 FINISHED
Object Earl of Pembroke
The Earl of Pembroke is a historic English peerage title associated with powerful medieval magnates who played prominent roles in royal politics, military campaigns, and governance.
E256385 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: Earl of Pembroke | Statement: [William of Valence, titleThroughMarriage, Earl of Pembroke]
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: Earl of Pembroke
Triple: [William of Valence, titleThroughMarriage, Earl of Pembroke]
Generated description
The Earl of Pembroke is a historic English peerage title associated with powerful medieval magnates who played prominent roles in royal politics, military campaigns, and governance.

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_69e2c4d76d148190b58ad612467149a5 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40fdcf6c8819080e2fb6001547d3b completed May 1, 2026, 2:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10679b2eb081908788851e1d9497a2 completed May 22, 2026, 2:26 p.m.
NEDg Description generation batch_6a106883259c8190a5cd5759a46c4c40 completed May 22, 2026, 2:30 p.m.
NED2 Entity disambiguation (via description) batch_6a106b36ea6481908bd4a4ead6b40818 completed May 22, 2026, 2:41 p.m.
Created at: April 18, 2026, 3:21 a.m.