Triple
T5661182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tri-Cities Airport |
E124743
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Pasco |
E311812
|
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: Pasco | Statement: [Tri-Cities Airport, serves, Pasco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasco Context triple: [Tri-Cities Airport, serves, Pasco]
-
A.
Pasco
chosen
Pasco is a city in southeastern Washington State that forms part of the Tri-Cities region along with Kennewick and Richland.
-
B.
Lakeland
Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
-
C.
Bradenton
Bradenton is a city on Florida’s Gulf Coast known for its waterfront location along the Manatee River and proximity to popular beaches and the Sarasota–Bradenton metropolitan area.
-
D.
Pasco Region
Pasco Region is an inland administrative region of central Peru known for its Andean highlands, mining activities, and diverse ecosystems ranging from mountains to cloud forests.
-
E.
Ocala
Ocala is a city in north-central Florida known for its thoroughbred horse farms and historic downtown.
- 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c0232077448190afdef460671eaf4f |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097d7e0fc81909f051f8789ef9fb9 |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:42 p.m.