Triple
T14125739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wupper basin |
E340025
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Haan |
E841021
|
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: Haan | Statement: [Wupper basin, containsTown, Haan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haan Context triple: [Wupper basin, containsTown, Haan]
-
A.
Haan
chosen
Haan is a town in the German state of North Rhine-Westphalia, known for its location between Düsseldorf and Wuppertal and its mix of residential areas and light industry.
-
B.
Hakha
Hakha is a hill town in western Myanmar that serves as the administrative and cultural center of the Chin people.
-
C.
Haenam
Haenam is a coastal county in South Jeolla Province, South Korea, known for being the country's southernmost mainland point and for its scenic agricultural landscapes.
-
D.
Haʻano
Haʻano is a small inhabited island in the Haʻapai group of Tonga, known for its traditional villages and quiet, rural character.
-
E.
Hahn
Hahn is a surname of German origin borne by various notable individuals across fields such as science, sports, and the arts.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6096976481909dc79066c5165a50 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0a7a7c8190860d8ce47b5f0732 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.