Triple
T7998749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andries Hendrik Potgieter |
E186191
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Andries |
E162902
|
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: Andries | Statement: [Andries Hendrik Potgieter, givenName, Andries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andries Context triple: [Andries Hendrik Potgieter, givenName, Andries]
-
A.
Andries
chosen
Andries is a Dutch given name traditionally used for men, equivalent to Andrew in English.
-
B.
Adriaan
Adriaan is a masculine given name of Dutch origin commonly used in the Netherlands and other Dutch-speaking regions.
-
C.
Wouter
Wouter is a Dutch historian of religion and leading scholar of Western esotericism.
-
D.
Andru
Andru is a diminutive form of the given name Andrei, typically used as an affectionate or informal nickname.
-
E.
Ozinga
Ozinga is a Dutch surname most notably associated with individuals such as Sjoukje Ozinga.
- 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c9a12788190a5607a538f4e07c1 |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe114372c819086f06e184d5ebde2 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:17 p.m.