Triple
T12650589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herborn |
E302146
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Dillenburg |
E170913
|
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: Dillenburg | Statement: [Herborn, locatedNear, Dillenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dillenburg Context triple: [Herborn, locatedNear, Dillenburg]
-
A.
Dillenburg
chosen
Dillenburg is a historic town in the German state of Hesse, known as the ancestral seat of the House of Orange-Nassau and its connection to Dutch history.
-
B.
Tecklenburg
Tecklenburg is a historic small town in North Rhine-Westphalia, Germany, known for its medieval architecture and open-air theater.
-
C.
Schwabhausen
Schwabhausen is a municipality in Bavaria, Germany, known for its rural character and location within the greater Munich metropolitan region.
-
D.
Neustadt
Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
-
E.
Neustadt
Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
- 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_69d9615f28cc81908e37249d7ab5ed74 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6719c18508190a9c28b2526e6b336 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:18 p.m.