Triple
T21285025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alblasserwaard |
E524632
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Nieuwpoort
Nieuwpoort is a small historic city in the Dutch province of South Holland, known for its well-preserved fortifications and picturesque setting along the River Lek.
|
E1476113
|
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: Nieuwpoort | Statement: [Alblasserwaard, contains, Nieuwpoort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nieuwpoort Context triple: [Alblasserwaard, contains, Nieuwpoort]
-
A.
Nieuwpoort
Nieuwpoort is a coastal town in West Flanders, Belgium, known for its historic harbor and its strategic role in World War I.
-
B.
Milport
Milport is a fictional British parliamentary constituency featured in Patrick O’Brian’s Aubrey–Maturin historical naval novels.
-
C.
Wilhelmshaven
Wilhelmshaven is a coastal city in northwestern Germany known for its major naval base and port on the North Sea.
-
D.
Terneuzen port
Terneuzen port is a major Dutch seaport and industrial hub on the Western Scheldt, known for its role in maritime trade and access to the Ghent–Terneuzen Canal.
-
E.
Holland-on-Sea
Holland-on-Sea is a coastal town in Essex, England, known for its quiet residential character and sandy beaches along the North Sea.
- 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: Nieuwpoort Triple: [Alblasserwaard, contains, Nieuwpoort]
Generated description
Nieuwpoort is a small historic city in the Dutch province of South Holland, known for its well-preserved fortifications and picturesque setting along the River Lek.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nieuwpoort Target entity description: Nieuwpoort is a small historic city in the Dutch province of South Holland, known for its well-preserved fortifications and picturesque setting along the River Lek.
-
A.
Nieuwpoort
Nieuwpoort is a coastal town in West Flanders, Belgium, known for its historic harbor and its strategic role in World War I.
-
B.
Milport
Milport is a fictional British parliamentary constituency featured in Patrick O’Brian’s Aubrey–Maturin historical naval novels.
-
C.
Wilhelmshaven
Wilhelmshaven is a coastal city in northwestern Germany known for its major naval base and port on the North Sea.
-
D.
Terneuzen port
Terneuzen port is a major Dutch seaport and industrial hub on the Western Scheldt, known for its role in maritime trade and access to the Ghent–Terneuzen Canal.
-
E.
Holland-on-Sea
Holland-on-Sea is a coastal town in Essex, England, known for its quiet residential character and sandy beaches along the North Sea.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d658e08190ad2f267123d53ede |
completed | April 21, 2026, 8:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09980794088190a54f7f00c2d3b3fb |
completed | May 17, 2026, 10:27 a.m. |
| NEDg | Description generation | batch_6a0998a3326481908a4dfddfb7b2ecd9 |
completed | May 17, 2026, 10:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09996c8d7c81908cc9874f6e1a3fff |
completed | May 17, 2026, 10:33 a.m. |
Created at: April 16, 2026, 4:03 p.m.