Triple

T6693624
Position Surface form Disambiguated ID Type / Status
Subject Dallas urban area E152689 entity
Predicate hasSuburb P747 FINISHED
Object Celina
Celina is a rapidly growing suburban city in the northern part of the Dallas–Fort Worth metropolitan area in Texas.
 E611709 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: Celina | Statement: [Dallas urban area, hasSuburb, Celina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Celina
Context triple: [Dallas urban area, hasSuburb, Celina]
  • A. Bella Vista
    Bella Vista is a historic, culturally vibrant neighborhood in South Philadelphia known for its Italian Market and diverse dining scene.
  • B. Bella Vista
    Bella Vista is a small unincorporated community in Northern California’s Shasta County, known for its rural setting near Redding.
  • C. McKinney
    McKinney is a surname of Scottish and Irish origin borne by various notable individuals, including American politician and activist Cynthia McKinney.
  • D. Loveland
    Loveland is a city in northern Colorado known for its art community, sculpture parks, and proximity to the Rocky Mountains.
  • E. Carrington
    Carrington is a surname of English origin borne by various notable individuals across politics, the military, the arts, and other fields.
  • 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: Celina
Triple: [Dallas urban area, hasSuburb, Celina]
Generated description
Celina is a rapidly growing suburban city in the northern part of the Dallas–Fort Worth metropolitan area in Texas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Celina
Target entity description: Celina is a rapidly growing suburban city in the northern part of the Dallas–Fort Worth metropolitan area in Texas.
  • A. Bella Vista
    Bella Vista is a historic, culturally vibrant neighborhood in South Philadelphia known for its Italian Market and diverse dining scene.
  • B. Bella Vista
    Bella Vista is a small unincorporated community in Northern California’s Shasta County, known for its rural setting near Redding.
  • C. McKinney
    McKinney is a surname of Scottish and Irish origin borne by various notable individuals, including American politician and activist Cynthia McKinney.
  • D. Loveland
    Loveland is a city in northern Colorado known for its art community, sculpture parks, and proximity to the Rocky Mountains.
  • E. Carrington
    Carrington is a surname of English origin borne by various notable individuals across politics, the military, the arts, and other fields.
  • 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_69c6880687b08190805278b504d1c92c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6b1955e448190adbfed7dc28f8c52 completed March 27, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7b97210819086e88624c476fa24 completed March 27, 2026, 9:33 p.m.
NEDg Description generation batch_69c6f8955748819092b0e51cff6cab69 completed March 27, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_69c6f9441d74819098f0639a29fdeb5e completed March 27, 2026, 9:40 p.m.
Created at: March 27, 2026, 2:05 p.m.