Triple
T3874801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnsberg region |
E92473
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Herne |
E355366
|
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: Herne | Statement: [Arnsberg region, contains, Herne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herne Context triple: [Arnsberg region, contains, Herne]
-
A.
Herne
chosen
Herne is a city in the Ruhr area of North Rhine-Westphalia, Germany, known for its industrial heritage and dense urban character.
-
B.
Herne Hill
Herne Hill is a residential district in South London known for its Victorian architecture, local markets, and proximity to Brockwell Park.
-
C.
Reydon
Reydon is a village and civil parish in the English county of Suffolk, located near the coastal town of Southwold.
-
D.
Blackheath
Blackheath is a historic village and popular tourist stop in the Blue Mountains of New South Wales, Australia, known for its dramatic cliffs, lookouts, and bushwalking trails.
-
E.
Larkfield
Larkfield is a village and civil parish in Kent, England, situated within the Tonbridge and Malling district.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec59bea08190b1e193f34944a2ee |
completed | March 9, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c87214881908e03f5c770c58713 |
completed | March 14, 2026, 8:29 a.m. |
Created at: March 9, 2026, 3:20 p.m.