Triple
T22787678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vélizy-Villacoublay |
E564013
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Dietzenbach |
—
|
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: Dietzenbach | Statement: [Vélizy-Villacoublay, hasTwinTown, Dietzenbach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dietzenbach Context triple: [Vélizy-Villacoublay, hasTwinTown, Dietzenbach]
-
A.
Dietzenbach
chosen
Dietzenbach is a town in the state of Hesse in central Germany, located near Frankfurt am Main.
-
B.
Deisenhausen
Deisenhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
C.
Vellinghausen
Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
-
D.
Donsbach
Donsbach is a village and district of the town of Dillenburg in the Lahn-Dill-Kreis region of Hesse, Germany.
-
E.
Bardüttingdorf
Bardüttingdorf is a village-level district that forms part of the town of Spenge in North Rhine-Westphalia, Germany.
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c32de6481909ef358d16de98496 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 3:29 p.m.