Triple
T14866567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gellért Monument |
E349629
|
entity |
| Predicate | sculptor |
P184
|
FINISHED |
| Object |
Gyula Jankovits
Gyula Jankovits was a Hungarian sculptor best known for creating prominent public monuments in Budapest, including the Gellért Monument.
|
E1140054
|
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: Gyula Jankovits | Statement: [Gellért Monument, sculptor, Gyula Jankovits]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gyula Jankovits Context triple: [Gellért Monument, sculptor, Gyula Jankovits]
-
A.
József Takács
József Takács is a Hungarian footballer known for his contributions to early 20th-century Hungarian club and national teams.
-
B.
László Papp
László Papp was a legendary Hungarian boxer who became the first boxer to win three consecutive Olympic gold medals.
-
C.
László Takács
László Takács is a Hungarian mathematician known for his contributions to probability theory and queueing theory.
-
D.
Gyula Pados
Gyula Pados is a Hungarian cinematographer known for his visually dynamic work on international films such as "Million Dollar Arm," "Predators," and "Maze Runner: The Scorch Trials."
-
E.
László Kovács
László Kovács was a renowned Hungarian-American cinematographer celebrated for his influential work in New Hollywood cinema, including landmark films of the late 1960s and 1970s.
- 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: Gyula Jankovits Triple: [Gellért Monument, sculptor, Gyula Jankovits]
Generated description
Gyula Jankovits was a Hungarian sculptor best known for creating prominent public monuments in Budapest, including the Gellért Monument.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gyula Jankovits Target entity description: Gyula Jankovits was a Hungarian sculptor best known for creating prominent public monuments in Budapest, including the Gellért Monument.
-
A.
József Takács
József Takács is a Hungarian footballer known for his contributions to early 20th-century Hungarian club and national teams.
-
B.
László Papp
László Papp was a legendary Hungarian boxer who became the first boxer to win three consecutive Olympic gold medals.
-
C.
László Takács
László Takács is a Hungarian mathematician known for his contributions to probability theory and queueing theory.
-
D.
Gyula Pados
Gyula Pados is a Hungarian cinematographer known for his visually dynamic work on international films such as "Million Dollar Arm," "Predators," and "Maze Runner: The Scorch Trials."
-
E.
László Kovács
László Kovács was a renowned Hungarian-American cinematographer celebrated for his influential work in New Hollywood cinema, including landmark films of the late 1960s and 1970s.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5761c688190b4477cb081554b51 |
completed | April 15, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfd1a1b48190b3b69b2841f643a3 |
completed | May 9, 2026, 5:02 a.m. |
| NEDg | Description generation | batch_69fec17d53448190942e5df10ffad4e5 |
completed | May 9, 2026, 5:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fec2300c4481908892a6515d99c12f |
completed | May 9, 2026, 5:12 a.m. |
Created at: April 10, 2026, 1:55 a.m.