Triple

T6410457
Position Surface form Disambiguated ID Type / Status
Subject Alabama's 3rd congressional district E127690 entity
Predicate containsCity P294 FINISHED
Object Ashland, Alabama
Ashland, Alabama is a small city in Clay County that serves as the county seat and lies in east-central Alabama.
E643541 NE FINISHED

How this triple was built (4 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: Ashland, Alabama | Statement: [Alabama's 3rd congressional district, containsCity, Ashland, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashland, Alabama
Context triple: [Alabama's 3rd congressional district, containsCity, Ashland, Alabama]
  • A. Ashville, Alabama
    Ashville, Alabama is a small historic town in central Alabama that serves as one of the two county seats of St. Clair County.
  • B. Ashland, Mississippi
    Ashland, Mississippi is a small town in northern Mississippi that serves as the administrative and cultural center of Benton County.
  • C. Sylvania, Alabama
    Sylvania, Alabama is a small rural town in northeastern Alabama known for its close-knit community and location atop Sand Mountain.
  • D. Eldridge, Alabama
    Eldridge, Alabama is a small rural town located in Walker County in the northwestern part of the state.
  • E. Ensley, Alabama
    Ensley, Alabama is a historic industrial neighborhood in Birmingham that developed as a major steelmaking and manufacturing center in the late 19th and early 20th centuries.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Ashland, Alabama
Triple: [Alabama's 3rd congressional district, containsCity, Ashland, Alabama]
Generated description
Ashland, Alabama is a small city in Clay County that serves as the county seat and lies in east-central Alabama.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ashland, Alabama
Target entity description: Ashland, Alabama is a small city in Clay County that serves as the county seat and lies in east-central Alabama.
  • A. Ashville, Alabama
    Ashville, Alabama is a small historic town in central Alabama that serves as one of the two county seats of St. Clair County.
  • B. Ashland, Mississippi
    Ashland, Mississippi is a small town in northern Mississippi that serves as the administrative and cultural center of Benton County.
  • C. Sylvania, Alabama
    Sylvania, Alabama is a small rural town in northeastern Alabama known for its close-knit community and location atop Sand Mountain.
  • D. Eldridge, Alabama
    Eldridge, Alabama is a small rural town located in Walker County in the northwestern part of the state.
  • E. Ensley, Alabama
    Ensley, Alabama is a historic industrial neighborhood in Birmingham that developed as a major steelmaking and manufacturing center in the late 19th and early 20th centuries.
  • F. None of above. chosen

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_69c0083723d88190b1e37b19df162c08 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068cf81508190bc09e58ec45bc858 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a303b960819082981f0efbdce014 completed March 28, 2026, 9:44 a.m.
NEDg Description generation batch_69c7a446c5088190908dd7b4cdc57f18 completed March 28, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_69c7a4fc9f788190b38437c6e91a5f8a completed March 28, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:41 p.m.