Triple
T15981312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Leven |
E387581
|
entity |
| Predicate | hasSettlementOnBank |
P1010
|
FINISHED |
| Object | Renton |
E572429
|
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: Renton | Statement: [River Leven, hasSettlementOnBank, Renton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Renton Context triple: [River Leven, hasSettlementOnBank, Renton]
-
A.
Renton
chosen
Renton is a small town in West Dunbartonshire, Scotland, situated on the River Leven between Dumbarton and Alexandria.
-
B.
Renton
Renton is a suburban city in Washington State located just southeast of Seattle, known for its Boeing facilities and position at the south end of Lake Washington.
-
C.
Tukwila
Tukwila is a suburban city just south of Seattle, Washington, known as a regional transportation and retail hub.
-
D.
Kirkland
Kirkland is a surname most notably associated with American ballerina Gelsey Kirkland.
-
E.
Kirkland
Kirkland is a suburban city on the eastern shore of Lake Washington in Washington State, known for its waterfront parks, vibrant downtown, and role as part of the Seattle metropolitan area.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15754e8648190a93b73184db089a7 |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084a6d6308190ad57a51b380171a2 |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 4:54 a.m.