Triple
T10088607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Link 2 Line |
E215283
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Bellevue |
unclear NED1
|
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: Bellevue | Statement: [Link 2 Line, serves, Bellevue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bellevue Context triple: [Link 2 Line, serves, Bellevue]
-
A.
Bellevue
Bellevue is a small municipality located along Lake Geneva in the canton of Geneva in southwestern Switzerland.
-
B.
Bellevue
Bellevue is a scenic mountain station in the French Alps that serves as a popular starting point for hikes and ascents around Mont Blanc.
-
C.
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.
-
D.
Bellevue
Bellevue is a major city in Washington State’s Seattle metropolitan area, known for its thriving downtown, tech industry presence, and high quality of life.
-
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. chosen
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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd057e32881908bf630559af94906 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3734e5e688190bbfa472547ef65e8 |
completed | April 18, 2026, 12:04 p.m. |
Created at: March 30, 2026, 9:01 p.m.