Triple
T19856608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Lorraine |
E477147
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Bar |
—
|
NE NERFINISHED |
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: Bar | Statement: [Upper Lorraine, borderedBy, Bar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bar Context triple: [Upper Lorraine, borderedBy, Bar]
-
A.
Bar
Bar is a coastal city and major seaport in southern Montenegro on the Adriatic Sea.
-
B.
Bar
chosen
Bar is a small historic city in central-western Ukraine known for its strategic location and cultural heritage.
-
C.
Ban
Ban was a medieval noble title used in several Central and Southeast European states, often designating a high-ranking governor or viceroy.
-
D.
Ban
Ban was the nickname of Ban Johnson, the influential early 20th-century baseball executive who served as the first president of the American League.
-
E.
Baar
Baar is a municipality in the canton of Zug in central Switzerland, known for its favorable tax environment and mix of residential areas and international businesses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6586c14fc81908d34785f1088b0a9 |
completed | April 20, 2026, 4:46 p.m. |
Created at: April 10, 2026, 1:51 p.m.