Triple
T9436092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentan |
E227509
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Rotenburg an der Wümme |
E281706
|
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: Rotenburg an der Wümme | Statement: [Argentan, hasTwinTown, Rotenburg an der Wümme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rotenburg an der Wümme Context triple: [Argentan, hasTwinTown, Rotenburg an der Wümme]
-
A.
Rotenburg (Wümme)
chosen
Rotenburg (Wümme) is a small town in Lower Saxony, Germany, known for its rural surroundings and role as a local administrative and service center.
-
B.
Rotenburg an der Fulda
Rotenburg an der Fulda is a historic small town in northeastern Hesse, Germany, situated along the Fulda River and known for its well-preserved half-timbered architecture.
-
C.
Northeim
Northeim is a town in Lower Saxony, Germany, known for its medieval old town and location in the Leine River valley.
-
D.
Lüneburg
Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
-
E.
Helmstedt
Helmstedt is a historic town in Lower Saxony, Germany, known for its medieval architecture and former university.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7ede1e148190b5793863a851c92c |
completed | April 1, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2ffd03dac81909f6c91afb8d49521 |
completed | April 6, 2026, 12:35 a.m. |
Created at: March 30, 2026, 7:50 p.m.