Triple
T9703659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunaújváros |
E234840
|
entity |
| Predicate | hasFormerName |
P65
|
FINISHED |
| Object | Pentele |
E815472
|
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: Pentele | Statement: [Dunaújváros, hasFormerName, Pentele]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pentele Context triple: [Dunaújváros, hasFormerName, Pentele]
-
A.
Pentele
chosen
Pentele is the historical settlement that later developed into the modern Hungarian industrial city of Dunaújváros.
-
B.
Tapolca
Tapolca is a small Hungarian town in the Transdanubian region, known for its scenic karst landscape and the famous Tapolca Lake Cave.
-
C.
Pallatanga
Pallatanga is a rural town and canton in central Ecuador known for its agricultural activities and scenic Andean surroundings.
-
D.
Balka
Balka is a coastal village and beach area on the Danish island of Bornholm, known for its shallow, child-friendly sandy shoreline and holiday atmosphere.
-
E.
Pécel
Pécel is a town in central Hungary that functions as a suburban settlement near Budapest within Pest County.
- 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_69ca84cc78808190a56f3402b7c139a7 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d73a0148190ad4178fd462cdd9c |
completed | April 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19f800ec48190bc3028ecb3baeb28 |
completed | April 4, 2026, 11:32 p.m. |
Created at: March 30, 2026, 8:18 p.m.