Triple
T9749638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homberg/Ruhrort/Baerl |
E236406
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Homberg
Homberg is a district of the German city of Duisburg, located on the western bank of the Rhine in the state of North Rhine-Westphalia.
|
E850495
|
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: Homberg | Statement: [Homberg/Ruhrort/Baerl, hasPart, Homberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Homberg Context triple: [Homberg/Ruhrort/Baerl, hasPart, Homberg]
-
A.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
B.
Nordhausen
Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
-
C.
Holthausen
Holthausen is a district of the German town of Hattingen in North Rhine-Westphalia.
-
D.
Suhl
Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
-
E.
Staßfurt
Staßfurt is a town in Saxony-Anhalt, Germany, historically known for its salt mining and chemical industry.
- 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: Homberg Triple: [Homberg/Ruhrort/Baerl, hasPart, Homberg]
Generated description
Homberg is a district of the German city of Duisburg, located on the western bank of the Rhine in the state of North Rhine-Westphalia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Homberg Target entity description: Homberg is a district of the German city of Duisburg, located on the western bank of the Rhine in the state of North Rhine-Westphalia.
-
A.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
B.
Nordhausen
Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
-
C.
Holthausen
Holthausen is a district of the German town of Hattingen in North Rhine-Westphalia.
-
D.
Suhl
Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
-
E.
Staßfurt
Staßfurt is a town in Saxony-Anhalt, Germany, historically known for its salt mining and chemical industry.
- 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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f6a2f8c8190a6f6af6587ee90b8 |
completed | April 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a77b6fac81909a9b0998f5dd1e58 |
completed | April 8, 2026, 7:07 p.m. |
| NEDg | Description generation | batch_69d6aac2dc4c819088a8c29d604cf9ce |
completed | April 8, 2026, 7:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6d02015bc8190a7041a7d725c8a1b |
completed | April 8, 2026, 10:01 p.m. |
Created at: March 30, 2026, 8:24 p.m.