Triple
T6625900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menden |
E149798
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object |
Halingen
Halingen is a suburban district of the town of Menden in North Rhine-Westphalia, Germany.
|
E607462
|
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: Halingen | Statement: [Menden, hasSuburb, Halingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halingen Context triple: [Menden, hasSuburb, Halingen]
-
A.
Henningsvær
Henningsvær is a picturesque fishing village in northern Norway, known for its traditional architecture, dramatic coastal scenery, and vibrant arts and tourism scene.
-
B.
Skudeneshavn
Skudeneshavn is a historic coastal town in southwestern Norway known for its well-preserved wooden architecture and maritime heritage.
-
C.
Haugesund
Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
-
D.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
E.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and 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: Halingen Triple: [Menden, hasSuburb, Halingen]
Generated description
Halingen is a suburban district of the town of Menden in North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Halingen Target entity description: Halingen is a suburban district of the town of Menden in North Rhine-Westphalia, Germany.
-
A.
Henningsvær
Henningsvær is a picturesque fishing village in northern Norway, known for its traditional architecture, dramatic coastal scenery, and vibrant arts and tourism scene.
-
B.
Skudeneshavn
Skudeneshavn is a historic coastal town in southwestern Norway known for its well-preserved wooden architecture and maritime heritage.
-
C.
Haugesund
Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
-
D.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
E.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af8187d881908b7a86f2cae5de23 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e44d356c8190ad4f2a617c3de4af |
completed | March 27, 2026, 8:10 p.m. |
| NEDg | Description generation | batch_69c6e5b236888190b108de51c730179a |
completed | March 27, 2026, 8:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6e7ce9aa88190abd000a13c00a070 |
completed | March 27, 2026, 8:25 p.m. |
Created at: March 27, 2026, 1:58 p.m.