Triple
T3970920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Applause |
E92332
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object |
Karl Hajos
Karl Hajos was a Hungarian-American composer best known for his film scores during the early sound era of Hollywood cinema.
|
E404515
|
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: Karl Hajos | Statement: [Applause, composer, Karl Hajos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karl Hajos Context triple: [Applause, composer, Karl Hajos]
-
A.
Alfréd Hajós
Alfréd Hajós was a Hungarian swimmer and architect who became one of the first modern Olympic champions by winning multiple gold medals at the inaugural 1896 Games.
-
B.
Laszlo Molnar
Laszlo Molnar is a software developer and author known for creating the UPX (Ultimate Packer for Executables) executable compression tool.
-
C.
Ludwig Ruff
Ludwig Ruff was a German architect known for his monumental Nazi-era designs, including major projects in Nuremberg.
-
D.
Josef Bühler
Josef Bühler was a high-ranking Nazi official and lawyer who served as State Secretary in the General Government of occupied Poland and played a key role in implementing the Holocaust.
-
E.
Emil Seidel
Emil Seidel was an American socialist politician best known as the first Socialist mayor of a major U.S. city, Milwaukee, in the early 20th century.
- 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: Karl Hajos Triple: [Applause, composer, Karl Hajos]
Generated description
Karl Hajos was a Hungarian-American composer best known for his film scores during the early sound era of Hollywood cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karl Hajos Target entity description: Karl Hajos was a Hungarian-American composer best known for his film scores during the early sound era of Hollywood cinema.
-
A.
Alfréd Hajós
Alfréd Hajós was a Hungarian swimmer and architect who became one of the first modern Olympic champions by winning multiple gold medals at the inaugural 1896 Games.
-
B.
Laszlo Molnar
Laszlo Molnar is a software developer and author known for creating the UPX (Ultimate Packer for Executables) executable compression tool.
-
C.
Ludwig Ruff
Ludwig Ruff was a German architect known for his monumental Nazi-era designs, including major projects in Nuremberg.
-
D.
Josef Bühler
Josef Bühler was a high-ranking Nazi official and lawyer who served as State Secretary in the General Government of occupied Poland and played a key role in implementing the Holocaust.
-
E.
Emil Seidel
Emil Seidel was an American socialist politician best known as the first Socialist mayor of a major U.S. city, Milwaukee, in the early 20th century.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef995d27881908b24a5b2ef57455f |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5400b75d081909b8e4840b15d19f1 |
completed | March 14, 2026, 11:01 a.m. |
| NEDg | Description generation | batch_69b540eb53788190aa281ee38edc1729 |
completed | March 14, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b541a55cb081909ec1f87a7553b6f2 |
completed | March 14, 2026, 11:08 a.m. |
Created at: March 9, 2026, 3:32 p.m.