Triple
T12335073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tadeusz Boy-Żeleński |
E294062
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Żeleński
Żeleński is a Polish surname most notably associated with Tadeusz Boy-Żeleński, a prominent writer, critic, and translator of French literature.
|
E983088
|
NE FINISHED |
How this triple was built (4 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: Żeleński | Statement: [Tadeusz Boy-Żeleński, familyName, Żeleński]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Żeleński Context triple: [Tadeusz Boy-Żeleński, familyName, Żeleński]
-
A.
Korzeniowski
Korzeniowski is a Polish surname most notably borne by contemporary film and television composer Abel Korzeniowski.
-
B.
Żółkiewski
Żółkiewski is a Polish noble surname most famously associated with the hetman and statesman Stanisław Żółkiewski of the Polish–Lithuanian Commonwealth.
-
C.
Leszczyński
Leszczyński is a Polish noble surname most famously borne by Stanisław Leszczyński, a former King of Poland and Duke of Lorraine.
-
D.
Wasilewski
Wasilewski is a Polish surname, typically indicating familial or geographic origin and commonly found in Poland and among the Polish diaspora.
-
E.
Zawisza
Zawisza is a Polish surname historically associated with several notable figures, including nobles, politicians, and cultural personalities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Żeleński Triple: [Tadeusz Boy-Żeleński, familyName, Żeleński]
Generated description
Żeleński is a Polish surname most notably associated with Tadeusz Boy-Żeleński, a prominent writer, critic, and translator of French literature.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Żeleński Target entity description: Żeleński is a Polish surname most notably associated with Tadeusz Boy-Żeleński, a prominent writer, critic, and translator of French literature.
-
A.
Korzeniowski
Korzeniowski is a Polish surname most notably borne by contemporary film and television composer Abel Korzeniowski.
-
B.
Żółkiewski
Żółkiewski is a Polish noble surname most famously associated with the hetman and statesman Stanisław Żółkiewski of the Polish–Lithuanian Commonwealth.
-
C.
Leszczyński
Leszczyński is a Polish noble surname most famously borne by Stanisław Leszczyński, a former King of Poland and Duke of Lorraine.
-
D.
Wasilewski
Wasilewski is a Polish surname, typically indicating familial or geographic origin and commonly found in Poland and among the Polish diaspora.
-
E.
Zawisza
Zawisza is a Polish surname historically associated with several notable figures, including nobles, politicians, and cultural personalities.
- F. None of above. chosen
Provenance (5 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f6683e881908920e1fee02a14e3 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63ef164508190bc311a8199cfbc70 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f6400fe9888190ae8244ccc8e8bc39 |
completed | May 2, 2026, 6:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6416d02008190a9e36658d7194787 |
completed | May 2, 2026, 6:24 p.m. |
Created at: April 8, 2026, 9:53 p.m.