Triple
T12644448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarreguemines |
E301984
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Eisenhüttenstadt |
E277662
|
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: Eisenhüttenstadt | Statement: [Sarreguemines, hasTwinTown, Eisenhüttenstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eisenhüttenstadt Context triple: [Sarreguemines, hasTwinTown, Eisenhüttenstadt]
-
A.
Eisenhüttenstadt
chosen
Eisenhüttenstadt is an industrial planned city in eastern Germany, known for its large steelworks and postwar socialist urban design.
-
B.
Cottbus
Cottbus is a city in eastern Germany known as a regional center for science and technology, including aerospace research.
-
C.
Mahlsdorf
Mahlsdorf is a locality in the borough of Marzahn-Hellersdorf in eastern Berlin, Germany, known for its residential character and historic village center.
-
D.
Zwickau
Zwickau is a city in the German state of Saxony known historically as an important center of the automotive industry and as the birthplace of composer Robert Schumann.
-
E.
Leipzig
Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9614bf2f881909976becdf747f4fb |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d6d4bd8819087902472e77e0d38 |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 9, 2026, 5:17 p.m.