Triple
T22950097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alzette |
E569988
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Schifflange |
—
|
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: Schifflange | Statement: [Alzette, passesNear, Schifflange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schifflange Context triple: [Alzette, passesNear, Schifflange]
-
A.
Schifflange
chosen
Schifflange is a town and commune in southwestern Luxembourg known for its industrial heritage and proximity to the country’s second-largest city, Esch-sur-Alzette.
-
B.
Langenbach
Langenbach is a municipality in Bavaria, Germany, situated in the Freising district north of Munich.
-
C.
Langenbach
Langenbach is a locality that forms one of the subdivisions of the town of Vöhrenbach in the Black Forest region of southwestern Germany.
-
D.
Bad Schussenried
Bad Schussenried is a spa town in southern Germany known for its historic monastery complex and scenic location in Upper Swabia.
-
E.
Schiltach
Schiltach is a small historic town in Germany’s Black Forest region, known for its well-preserved half-timbered houses and picturesque riverside setting.
- 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181a085188190b06ffa227087302d |
completed | April 29, 2026, 3:57 a.m. |
Created at: April 17, 2026, 3:46 p.m.