Triple

T29167769
Position Surface form Disambiguated ID Type / Status
Subject District 9 Council seat E739368 entity
Predicate electoralDistrict P9598 FINISHED
Object Tulsa City Council District 9
Tulsa City Council District 9 is a municipal electoral district in Tulsa, Oklahoma, represented by one member on the Tulsa City Council.
E1861365 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: Tulsa City Council District 9 | Statement: [District 9 Council seat, electoralDistrict, Tulsa City Council District 9]
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: Tulsa City Council District 9
Triple: [District 9 Council seat, electoralDistrict, Tulsa City Council District 9]
Generated description
Tulsa City Council District 9 is a municipal electoral district in Tulsa, Oklahoma, represented by one member on the Tulsa City Council.

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_69f07cb6394c8190ab7842c48e699e2a completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f662d73ac8819084ad24fb84e85f35 completed May 2, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a843d954819083715f7fda242908 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25ac482b2c8190b29f490879ef6ea6 completed June 7, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a25b03453348190952e1ebd49c800b9 completed June 7, 2026, 5:53 p.m.
Created at: April 28, 2026, 11:51 a.m.