Triple
T1695019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krefeld |
E36636
|
entity |
| Predicate | hasCityDistrict |
P2709
|
FINISHED |
| Object |
Hüls
Hüls is a district of the German city of Krefeld in North Rhine-Westphalia, known for its historic town center and textile-industry heritage.
|
E192632
|
NE FINISHED |
How this triple was built (4 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: Hüls | Statement: [Krefeld, hasCityDistrict, Hüls]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hüls Context triple: [Krefeld, hasCityDistrict, Hüls]
-
A.
Winschoten
Winschoten is a town in the northeast of the Netherlands known historically as a regional trade center and for its traditional windmills and Jewish heritage.
-
B.
Wassenaar
Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
-
C.
Arnhemmer
An Arnhemmer is a resident or native of the Dutch city of Arnhem in the province of Gelderland.
-
D.
Heezen
Heezen is a surname most notably associated with American geologist and oceanographer Bruce C. Heezen, a pioneer in mapping the ocean floor.
-
E.
Soest
Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hüls Triple: [Krefeld, hasCityDistrict, Hüls]
Generated description
Hüls is a district of the German city of Krefeld in North Rhine-Westphalia, known for its historic town center and textile-industry heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hüls Target entity description: Hüls is a district of the German city of Krefeld in North Rhine-Westphalia, known for its historic town center and textile-industry heritage.
-
A.
Winschoten
Winschoten is a town in the northeast of the Netherlands known historically as a regional trade center and for its traditional windmills and Jewish heritage.
-
B.
Wassenaar
Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
-
C.
Arnhemmer
An Arnhemmer is a resident or native of the Dutch city of Arnhem in the province of Gelderland.
-
D.
Heezen
Heezen is a surname most notably associated with American geologist and oceanographer Bruce C. Heezen, a pioneer in mapping the ocean floor.
-
E.
Soest
Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
- F. None of above. chosen
Provenance (5 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62b3b8908190afc3f9e4a384684f |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ac9ed2c81909fe3fe40515526de |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad9575acf88190aa3fe80794534dd4 |
completed | March 8, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad97a7128c819097ff36216f00d4f9 |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 4, 2026, 7:30 p.m.