Triple
T22859674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorze River |
E566879
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Baar |
—
|
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: Baar | Statement: [Lorze River, passesThrough, Baar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baar Context triple: [Lorze River, passesThrough, Baar]
-
A.
Baar
chosen
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.
-
B.
Baar
Baar is a historical region in southwestern Germany, situated between the Black Forest and the Swabian Jura.
-
C.
Barcha
Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
-
D.
Barrin
Barrin is a French surname historically associated with notable figures such as Roland-Michel Barrin de La Galissonière, an 18th-century naval officer and colonial administrator.
-
E.
Bar
Bar is a small historic city in central-western Ukraine known for its strategic location and cultural heritage.
- 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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17ec082c08190943e6cfc2e25c5cc |
completed | April 29, 2026, 3:45 a.m. |
Created at: April 17, 2026, 3:37 p.m.