Triple
T6073792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waag (Amsterdam weighing house) |
E135347
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Waag |
E323136
|
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: Waag | Statement: [Waag (Amsterdam weighing house), hasName, Waag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waag Context triple: [Waag (Amsterdam weighing house), hasName, Waag]
-
A.
Waag
chosen
Waag is a historic weighing house located on the Grote Markt, notable for its traditional role in trade and its characteristic Dutch architecture.
-
B.
De Dam
De Dam is Amsterdam’s central and historic main square, known for its royal palace, national monument, and role as a major public gathering place.
-
C.
Woudenberg
Woudenberg is a small Dutch municipality and town located in the central Netherlands.
-
D.
De Wolden
De Wolden is a rural municipality in the northeastern Netherlands known for its scenic landscapes, small villages, and agricultural character.
-
E.
Waarder
Waarder is a small village in the Dutch province of South Holland, known for its rural character and traditional polder landscape.
- 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_69c00879e8048190b690717d19c5bc03 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0575b9bc08190a78b3082b9ccf00c |
completed | March 22, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d3fb99481909cc31c179eb4e8c9 |
completed | March 23, 2026, 11 a.m. |
Created at: March 22, 2026, 4:11 p.m.