Triple
T14643548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parádfürdő |
E343785
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Parád |
E1078690
|
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: Parád | Statement: [Parádfürdő, locatedNear, Parád]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parád Context triple: [Parádfürdő, locatedNear, Parád]
-
A.
Parád
chosen
Parád is a village and popular spa resort in northern Hungary, known for its mineral springs and scenic Mátra mountain surroundings.
-
B.
Putijarra
Putijarra is an Australian Aboriginal language traditionally spoken by the Martu people of the Western Desert region.
-
C.
Aragua
Aragua is a central Venezuelan state known for its diverse geography, which includes coastal areas, fertile valleys, and sections of the Cordillera de la Costa mountain range.
-
D.
Paranhos
Paranhos is a civil parish in the city of Porto, Portugal, known for its residential areas and several university and hospital facilities.
-
E.
Icó
Icó is a historic municipality in northeastern Brazil known for its colonial architecture and cultural heritage within the state of Ceará.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4e80aa48190884bab800f357106 |
completed | April 14, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde170d4a0819087caeacf39f95954 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:26 a.m.