Triple
T12086198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghent City Hall |
E287812
|
entity |
| Predicate | locatedAtStreet |
P959
|
FINISHED |
| Object |
Hoogpoort
Hoogpoort is a historic street in the center of Ghent, Belgium, known for its medieval architecture and important civic buildings.
|
E969026
|
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: Hoogpoort | Statement: [Ghent City Hall, locatedAtStreet, Hoogpoort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoogpoort Context triple: [Ghent City Hall, locatedAtStreet, Hoogpoort]
-
A.
Brouwersdam
Brouwersdam is a major Dutch dam and causeway in the Rhine–Meuse–Scheldt delta, built as part of the Delta Works to protect the Netherlands from North Sea flooding while supporting road traffic and water management.
-
B.
Woudenberg
Woudenberg is a small Dutch municipality and town located in the central Netherlands.
-
C.
Maasbracht
Maasbracht is a town in the Dutch province of Limburg, known as an inland port and industrial center along the River Meuse.
-
D.
Woudwetering
Woudwetering is a Dutch waterway in South Holland that serves as an important local canal near the village of Woubrugge.
-
E.
Everbeek
Everbeek is a village in the municipality of Brakel in East Flanders, Belgium, known for its rural landscape and wooded surroundings.
- 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: Hoogpoort Triple: [Ghent City Hall, locatedAtStreet, Hoogpoort]
Generated description
Hoogpoort is a historic street in the center of Ghent, Belgium, known for its medieval architecture and important civic buildings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hoogpoort Target entity description: Hoogpoort is a historic street in the center of Ghent, Belgium, known for its medieval architecture and important civic buildings.
-
A.
Brouwersdam
Brouwersdam is a major Dutch dam and causeway in the Rhine–Meuse–Scheldt delta, built as part of the Delta Works to protect the Netherlands from North Sea flooding while supporting road traffic and water management.
-
B.
Woudenberg
Woudenberg is a small Dutch municipality and town located in the central Netherlands.
-
C.
Maasbracht
Maasbracht is a town in the Dutch province of Limburg, known as an inland port and industrial center along the River Meuse.
-
D.
Woudwetering
Woudwetering is a Dutch waterway in South Holland that serves as an important local canal near the village of Woubrugge.
-
E.
Everbeek
Everbeek is a village in the municipality of Brakel in East Flanders, Belgium, known for its rural landscape and wooded surroundings.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91514c78c8190bc1cd569e524e8b4 |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a6d74888190aab150f1ceb2e9f1 |
completed | May 2, 2026, 2:30 p.m. |
| NEDg | Description generation | batch_69f60bda16e48190af8abc0aa8ef41f0 |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60cd1668881908f43d895fcfba0aa |
completed | May 2, 2026, 2:40 p.m. |
Created at: April 8, 2026, 9:48 p.m.