Triple
T8837301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drensteinfurt |
E210296
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Ahlen |
E668889
|
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: Ahlen | Statement: [Drensteinfurt, locatedNear, Ahlen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahlen Context triple: [Drensteinfurt, locatedNear, Ahlen]
-
A.
Ahlen
chosen
Ahlen is a mid-sized industrial town in the German state of North Rhine-Westphalia, known historically for coal mining and now for its diversified manufacturing sector.
-
B.
Iserlohn
Iserlohn is a city in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known historically for its role in World War II and its metalworking and industrial heritage.
-
C.
Hilden
Hilden is a town in western Germany’s North Rhine-Westphalia region, known for its proximity to Düsseldorf and its mix of residential, commercial, and light industrial areas.
-
D.
Furth
A Furth is a mountain in the British Isles outside Scotland that meets the height and prominence criteria to be classified similarly to a Scottish Munro.
-
E.
Borken
Borken is a town in western Germany that serves as an administrative and commercial center in the state of North Rhine-Westphalia.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc606adde08190825dbdabd199c025 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf898a478c81908f138a78f331b87d |
completed | April 3, 2026, 9:34 a.m. |
Created at: March 30, 2026, 6:48 p.m.