Triple
T10828169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambert Meertens |
E255545
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Meertens |
E255545
|
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: Meertens | Statement: [Lambert Meertens, familyName, Meertens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meertens Context triple: [Lambert Meertens, familyName, Meertens]
-
A.
Meertens
chosen
Meertens is a Dutch surname most notably associated with computer scientist Lambert Meertens, a key contributor to programming language design.
-
B.
Goudriaan
Goudriaan is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
-
C.
Berghuizen
Berghuizen is a small village located within the municipality of De Wolden in the Dutch province of Drenthe.
-
D.
Van der Madeweg
Van der Madeweg is a metro station in Amsterdam that serves as a stop on the city's rapid transit network.
-
E.
Meyer-Lübke
Meyer-Lübke is the surname of Wilhelm Meyer-Lübke, a prominent Swiss linguist known for his influential work in Romance philology.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734d3eab88190b30a3025b6b2b0bc |
completed | April 9, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de8592d8f08190ac577395ad7cc557 |
completed | April 14, 2026, 6:21 p.m. |
Created at: April 8, 2026, 9:19 p.m.