Triple
T22423543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pázmány Péter University |
E554307
|
entity |
| Predicate | hasCampus |
P116
|
FINISHED |
| Object | Piliscsaba |
E707132
|
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: Piliscsaba | Statement: [Pázmány Péter University, hasCampus, Piliscsaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Piliscsaba Context triple: [Pázmány Péter University, hasCampus, Piliscsaba]
-
A.
Piliscsaba
chosen
Piliscsaba is a town in Hungary known for its scenic setting near the Pilis Mountains and its role as a local educational and cultural center.
-
B.
Mundruczó
Mundruczó is the surname of Hungarian film and theatre director Kornél Mundruczó, known for his innovative and often provocative works.
-
C.
Tótkomlós
Tótkomlós is a small town in southeastern Hungary known for its agricultural surroundings and traditional rural character.
-
D.
Karcsag
Karcsag is a town in eastern Hungary known as the birthplace of Nobel Prize–winning biochemist Avram Hershko.
-
E.
Pusztamiske
Pusztamiske is a small village located in Veszprém County in western Hungary.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2af620819083338127e78137dc |
completed | April 29, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0af0f06cec8190a911ab9a867c0596 |
completed | May 18, 2026, 10:58 a.m. |
Created at: April 16, 2026, 8:47 p.m.