Triple
T15622839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis |
E375601
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Franciszek |
E289085
|
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: Franciszek | Statement: [Francis, relatedName, Franciszek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franciszek Context triple: [Francis, relatedName, Franciszek]
-
A.
Franciszek
chosen
Franciszek is a masculine given name of Latin origin, commonly used in Poland and other Slavic countries.
-
B.
Józef
Józef is a masculine given name of Hebrew origin, widely used in Poland and other Slavic countries as a form of Joseph.
-
C.
Lucjan
Lucjan is a masculine given name of Latin origin, commonly used in Poland and other Slavic countries.
-
D.
Paweł
Paweł is a common Polish given name, equivalent to the English name Paul.
-
E.
Timoteusz
Timoteusz is a masculine given name, primarily used in Polish and other Slavic languages, derived from the Greek-origin name Timothy.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9cfd94819091459aa17a002eaf |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff75655c948190aa1afa424e5270d1 |
completed | May 9, 2026, 5:56 p.m. |
Created at: April 10, 2026, 4:14 a.m.