Triple
T8927005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belltown |
E212560
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Downtown Seattle |
E37731
|
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: Downtown Seattle | Statement: [Belltown, partOf, Downtown Seattle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Downtown Seattle Context triple: [Belltown, partOf, Downtown Seattle]
-
A.
downtown Seattle
chosen
Downtown Seattle is the city’s central urban core, known for its dense cluster of offices, shops, cultural attractions, and waterfront views on Elliott Bay.
-
B.
Seattle
Seattle is a major coastal city in the U.S. state of Washington, known for its tech industry, vibrant music and arts scene, and iconic landmarks like the Space Needle.
-
C.
Bellevue
Bellevue is a small municipality located along Lake Geneva in the canton of Geneva in southwestern Switzerland.
-
D.
Bellevue
Bellevue is a Canadian television drama series starring Anna Paquin as a detective investigating the disappearance of a transgender teen in a small, tightly knit town.
-
E.
Bellevue
Bellevue is a city in eastern Nebraska, part of the Omaha metropolitan area and one of the state's oldest continuous settlements.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6671557c81909f3837ffd6a15ffe |
completed | April 1, 2026, 12:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1d55d84819094bc2b6e3dd94254 |
completed | April 3, 2026, 1:34 p.m. |
Created at: March 30, 2026, 6:57 p.m.