Triple

T28859949
Position Surface form Disambiguated ID Type / Status
Subject 2021 Arlington mayoral election E728830 entity
Predicate successorTo P78 FINISHED
Object 2018 Arlington mayoral election
The 2018 Arlington mayoral election was a local political contest in Arlington, Texas, to choose the city's mayor for the subsequent term.
E1835658 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: 2018 Arlington mayoral election | Statement: [2021 Arlington mayoral election, successorTo, 2018 Arlington mayoral election]
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: 2018 Arlington mayoral election
Triple: [2021 Arlington mayoral election, successorTo, 2018 Arlington mayoral election]
Generated description
The 2018 Arlington mayoral election was a local political contest in Arlington, Texas, to choose the city's mayor for the subsequent term.

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_69f031a01cbc8190ba87270bb6fe4639 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65a15e4c48190bcba6a5e930e2a9e completed May 2, 2026, 8:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bbc1cb80819085e68aa2607b0881 completed June 7, 2026, 12:30 a.m.
NEDg Description generation batch_6a24c01833908190a819592235484989 completed June 7, 2026, 12:49 a.m.
NED2 Entity disambiguation (via description) batch_6a24c43561d08190ac657094dbff3be7 completed June 7, 2026, 1:07 a.m.
Created at: April 28, 2026, 6:46 a.m.