Triple
T1696706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irena Komorowska |
E36673
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Komorowska
Komorowska is a Polish surname borne by various notable individuals in fields such as politics, arts, and academia.
|
E99281
|
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: Komorowska | Statement: [Irena Komorowska, familyName, Komorowska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Komorowska Context triple: [Irena Komorowska, familyName, Komorowska]
-
A.
Jaworzyna Krynicka
Jaworzyna Krynicka is a prominent mountain in southern Poland’s Beskid Sądecki range, known for its ski resort, hiking trails, and cable car access near the spa town of Krynica-Zdrój.
-
B.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
C.
Jastarnia
Jastarnia is a seaside resort town and fishing port on Poland’s Baltic coast, popular for its beaches and water sports.
-
D.
Kazimierz
Kazimierz is a historic district of Kraków known for its rich Jewish heritage, medieval architecture, and vibrant cultural life.
-
E.
Anna Maria Komorowska
Anna Maria Komorowska is a Polish-born aristocrat best known as the mother of Queen Mathilde of Belgium.
- 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: Komorowska Triple: [Irena Komorowska, familyName, Komorowska]
Generated description
Komorowska is a Polish surname borne by various notable individuals in fields such as politics, arts, and academia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Komorowska Target entity description: Komorowska is a Polish surname borne by various notable individuals in fields such as politics, arts, and academia.
-
A.
Jaworzyna Krynicka
Jaworzyna Krynicka is a prominent mountain in southern Poland’s Beskid Sądecki range, known for its ski resort, hiking trails, and cable car access near the spa town of Krynica-Zdrój.
-
B.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
C.
Jastarnia
Jastarnia is a seaside resort town and fishing port on Poland’s Baltic coast, popular for its beaches and water sports.
-
D.
Kazimierz
Kazimierz is a historic district of Kraków known for its rich Jewish heritage, medieval architecture, and vibrant cultural life.
-
E.
Anna Maria Komorowska
chosen
Anna Maria Komorowska is a Polish-born aristocrat best known as the mother of Queen Mathilde of Belgium.
- F. None of above.
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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62b78d20819096f0602058c46d8a |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad799ad838819087e945f47284a3b0 |
completed | March 8, 2026, 1:28 p.m. |
| NEDg | Description generation | batch_69ad81f90e948190b83078523b1cf3f8 |
completed | March 8, 2026, 2:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad82755910819087aa9940dc1e7495 |
completed | March 8, 2026, 2:06 p.m. |
Created at: March 4, 2026, 7:30 p.m.