Triple

T27266380
Position Surface form Disambiguated ID Type / Status
Subject John III of Navarre E687914 entity
Predicate title P38 FINISHED
Object Count of Périgord
The Count of Périgord was a noble title in medieval France associated with the lordship over the Périgord region, held at one point by John III of Navarre among other prominent aristocrats.
E1762869 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: Count of Périgord | Statement: [John III of Navarre, title, Count of Périgord]
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: Count of Périgord
Triple: [John III of Navarre, title, Count of Périgord]
Generated description
The Count of Périgord was a noble title in medieval France associated with the lordship over the Périgord region, held at one point by John III of Navarre among other prominent aristocrats.

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_69ef3557abc481908bf3c146f0f3356a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f626f39064819095a01840684caecc completed May 2, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12628966388190b8a992b91f3183d4 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a1263c16b7c8190bf1e6d9a48f04e79 completed May 24, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_6a12645e001081909536516633a422a9 completed May 24, 2026, 2:37 a.m.
Created at: April 27, 2026, 10:56 a.m.