Triple
T16338248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dries Mertens |
E396730
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Dries |
E636799
|
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: Dries | Statement: [Dries Mertens, givenName, Dries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dries Context triple: [Dries Mertens, givenName, Dries]
-
A.
Dries
chosen
Dries is a Dutch and Flemish masculine given name commonly used as a short form of Andries (Andrew).
-
B.
Driesh
Driesh is a prominent mountain in the Grampian range of Scotland, popular with hikers and often climbed alongside its neighboring peak, Mayar.
-
C.
Drees
Drees is a Dutch surname most notably associated with Willem Drees, a prominent 20th-century Dutch prime minister.
-
D.
Durst
Durst is a surname most prominently associated with the New York real estate–developing Durst family, including figures such as Joseph Durst and his descendants.
-
E.
Danneels
Danneels is a Belgian surname most notably associated with Cardinal Godfried Danneels, a prominent Roman Catholic prelate and former Archbishop of Mechelen-Brussels.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e6338081908aa03ee3dcbe5f70 |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00261b31c08190908a72bff20871be |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:07 a.m.