Triple
T8534234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nissewaard |
E202035
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Rijnmond |
E370216
|
NE FINISHED |
How this triple was built (2 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: Rijnmond | Statement: [Nissewaard, partOf, Rijnmond]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rijnmond Context triple: [Nissewaard, partOf, Rijnmond]
-
A.
Rijnmond
chosen
Rijnmond is a region in the western Netherlands centered around the port city of Rotterdam and the Rhine–Meuse river delta.
-
B.
Nieuwe Waterweg
Nieuwe Waterweg is a major artificial ship canal in the Netherlands that provides a direct deep-water connection between the North Sea and the port of Rotterdam.
-
C.
Drecht
Drecht is a lesser-known Dutch river whose waters help form the Amstel through their confluence.
-
D.
Pietermaai
Pietermaai is a historic waterfront neighborhood in Willemstad, Curaçao, known for its colorful colonial architecture, boutique hotels, and vibrant dining and nightlife scene.
-
E.
Damme
Damme is a town and municipality in the District of Vechta in Lower Saxony, Germany, known for its rural character and regional cultural traditions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca832355b08190b8b6a4ab4a4a3554 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6a0ccd4819097b41d0dfb1c5018 |
completed | March 31, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d7aa3a881909bfdd3536dbc4ec7 |
completed | April 2, 2026, 1:22 p.m. |
Created at: March 30, 2026, 6:17 p.m.