Triple

T29209407
Position Surface form Disambiguated ID Type / Status
Subject Jedi High Council E740504 entity
Predicate notableMember P10 FINISHED
Object Even Piell
Even Piell was a Lannik Jedi Master known for his fierce combat skills, distinctive scarred appearance, and service on the Jedi High Council during the final years of the Galactic Republic.
E1856105 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: Even Piell | Statement: [Jedi High Council, notableMember, Even Piell]
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: Even Piell
Triple: [Jedi High Council, notableMember, Even Piell]
Generated description
Even Piell was a Lannik Jedi Master known for his fierce combat skills, distinctive scarred appearance, and service on the Jedi High Council during the final years of the Galactic Republic.

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_69f07cb974108190b7e86ca489a6ebb6 completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f66403fce48190817d399195f1339a completed May 2, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2569c552bc81909fb36f99c0e4b91a completed June 7, 2026, 12:53 p.m.
NEDg Description generation batch_6a256dc27c708190b74c697d4eb1f0a2 completed June 7, 2026, 1:10 p.m.
NED2 Entity disambiguation (via description) batch_6a257303ae008190aad081788fc11925 completed June 7, 2026, 1:32 p.m.
Created at: April 28, 2026, 12:10 p.m.