Triple
T17998851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilfrid Michael Voynich |
E430571
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Telšiai |
E445267
|
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: Telšiai | Statement: [Wilfrid Michael Voynich, birthPlace, Telšiai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Telšiai Context triple: [Wilfrid Michael Voynich, birthPlace, Telšiai]
-
A.
Telšiai
chosen
Telšiai is a historic city in northwestern Lithuania that serves as the cultural and administrative center of the Samogitia region.
-
B.
Tauragė
Tauragė is a town in western Lithuania known as an administrative, cultural, and economic center of the surrounding region.
-
C.
Radviliškis
Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
-
D.
Vilkaviškis
Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
-
E.
Joniškis
Joniškis is a small town in northern Lithuania known for its historic architecture and cultural heritage, including well-preserved synagogues.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b3e6a2a881908af2d0a4a5053916 |
completed | April 19, 2026, 10:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b1ba79c8190b320d8071cae664d |
completed | May 14, 2026, 1:53 a.m. |
Created at: April 10, 2026, 10:23 a.m.