Triple
T8374634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saar |
E197544
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Völklingen |
E199323
|
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: Völklingen | Statement: [Saar, flowsThrough, Völklingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Völklingen Context triple: [Saar, flowsThrough, Völklingen]
-
A.
Völklingen
chosen
Völklingen is an industrial city in western Germany best known for its UNESCO-listed Völklingen Ironworks, a major preserved steelworks complex.
-
B.
Haguenau
Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
-
C.
Rolandseck
Rolandseck is a district of Remagen in Rhineland-Palatinate, Germany, known for its scenic location on the Rhine and its historic railway station and cultural venues.
-
D.
Breisach am Rhein
Breisach am Rhein is a historic German town on the Rhine River near the French border, known for its hilltop cathedral and strategic location between the Black Forest and Alsace.
-
E.
Schiltigheim
Schiltigheim is a suburban commune in northeastern France, located just north of Strasbourg and known historically for its brewing industry.
- 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_69ca82f56730819080cec5d991c76f4c |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80a996ec819083ce2607c0cdab7f |
completed | March 31, 2026, 8:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde7e7e7ac819084e82a98c4c1249e |
completed | April 2, 2026, 3:52 a.m. |
Created at: March 30, 2026, 6:01 p.m.