Triple
T12114410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juanita Beach Park |
E288517
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | City of Kirkland |
E974554
|
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: City of Kirkland | Statement: [Juanita Beach Park, operatedBy, City of Kirkland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Kirkland Context triple: [Juanita Beach Park, operatedBy, City of Kirkland]
-
A.
City of Kirkland
chosen
The City of Kirkland is a suburban city on the eastern shore of Lake Washington near Seattle, known for its waterfront parks, vibrant downtown, and residential neighborhoods like Juanita.
-
B.
City of Issaquah
The City of Issaquah is a suburban community in King County, Washington, nestled between the Issaquah Alps and Lake Sammamish and known for its outdoor recreation and rapid growth.
-
C.
City of Redmond
The City of Redmond is a municipal government in Washington State best known as the home of Microsoft and for its vibrant community events and parks.
-
D.
Kirkland
Kirkland is a suburban town located on the Island of Montreal in the Canadian province of Quebec.
-
E.
Kirkland
Kirkland is a surname most notably associated with American ballerina Gelsey Kirkland.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9156921dc8190aa132b0ab3a7c184 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a7fd708819090af422a60a69859 |
completed | May 2, 2026, 4:46 p.m. |
Created at: April 8, 2026, 9:49 p.m.