Triple

T28683702
Position Surface form Disambiguated ID Type / Status
Subject Seattle City Council District 3 E726071 entity
Predicate previouslyRepresentedBy P45113 FINISHED
Object Kshama Sawant
Kshama Sawant is a socialist politician and activist known for serving on the Seattle City Council and championing causes such as a $15 minimum wage and tenants’ rights.
E1828080 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: Kshama Sawant | Statement: [Seattle City Council District 3, previouslyRepresentedBy, Kshama Sawant]
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: Kshama Sawant
Triple: [Seattle City Council District 3, previouslyRepresentedBy, Kshama Sawant]
Generated description
Kshama Sawant is a socialist politician and activist known for serving on the Seattle City Council and championing causes such as a $15 minimum wage and tenants’ rights.

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_69f01d867608819086bc3e6b4f9de866 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f6567f9058819085754d42f495f9ec completed May 2, 2026, 7:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc3ac5cf8819080560b26a34d351c completed May 31, 2026, 11:26 p.m.
NEDg Description generation batch_6a1cc46491208190b29352509e2dbc79 completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc4ff58dc8190a81f7ad27e6b6fa8 completed May 31, 2026, 11:32 p.m.
Created at: April 28, 2026, 5:10 a.m.