Triple

T9626199
Position Surface form Disambiguated ID Type / Status
Subject Kingsessing E232471 entity
Predicate adjacentTo P224 FINISHED
Object Cedar Park E117291 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: Cedar Park | Statement: [Kingsessing, adjacentTo, Cedar Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cedar Park
Context triple: [Kingsessing, adjacentTo, Cedar Park]
  • A. Cedar Park chosen
    Cedar Park is a residential neighborhood in West Philadelphia known for its historic Victorian homes, diverse community, and proximity to the University of Pennsylvania.
  • B. Cedar Park, Texas
    Cedar Park, Texas is a fast-growing suburban city in the Austin metropolitan area known for its family-friendly neighborhoods, quality schools, and proximity to major tech employers.
  • C. Duncanville
    Duncanville is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas.
  • D. Balch Springs
    Balch Springs is a suburban city in the Dallas–Fort Worth metropolitan area in northeastern Texas.
  • E. Pflugerville, Texas
    Pflugerville, Texas is a rapidly growing suburban city in the Austin metropolitan area known for its family-friendly neighborhoods, schools, and recreational amenities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca848793ec8190a93a12383a754dc0 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9afc9144819084b208c3d04174ba completed April 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcb3a1ec819099c8a222c01c9d65 completed April 5, 2026, 1:36 a.m.
Created at: March 30, 2026, 8:10 p.m.