Triple
T8937988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin-Lichtenberg |
E212823
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Hennigsdorf |
E213861
|
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: Hennigsdorf | Statement: [Berlin-Lichtenberg, hasTwinTown, Hennigsdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hennigsdorf Context triple: [Berlin-Lichtenberg, hasTwinTown, Hennigsdorf]
-
A.
Hennigsdorf
chosen
Hennigsdorf is a town in the German state of Brandenburg, located just northwest of Berlin and known for its industrial heritage and proximity to the Havel River.
-
B.
Heinersdorf
Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
-
C.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
D.
Bohnsdorf
Bohnsdorf is a residential locality in the southeastern part of Berlin, Germany, known for its suburban character and proximity to the city’s green and lake-rich areas.
-
E.
Hermsdorf
Hermsdorf is a residential locality in the Berlin borough of Reinickendorf, known for its green surroundings and village-like character on the city’s northern edge.
- 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66b57a348190979effe4f9998eb7 |
completed | April 1, 2026, 12:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0b165fb0c81908c79b6ade3cca20e |
completed | April 4, 2026, 6:36 a.m. |
Created at: March 30, 2026, 6:58 p.m.