Triple
T15103364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budapest Metro Line 4 |
E360724
|
entity |
| Predicate | connectsDistrict |
P2564
|
FINISHED |
| Object | Kelenföld area |
E1081659
|
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: Kelenföld area | Statement: [Budapest Metro Line 4, connectsDistrict, Kelenföld area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kelenföld area Context triple: [Budapest Metro Line 4, connectsDistrict, Kelenföld area]
-
A.
Népliget area
The Népliget area is a large public park and transport hub in Budapest, Hungary, known for its green spaces, sports facilities, and major international bus station.
-
B.
Kelenföld
chosen
Kelenföld is a residential and transport hub neighborhood in southwestern Budapest, known for its major railway and metro interchange and large housing estates.
-
C.
Hollókő
Hollókő is a UNESCO World Heritage-listed Hungarian village renowned for its well-preserved traditional Palóc architecture and living rural culture.
-
D.
Lehel tér
Lehel tér is a major square and transport hub in Budapest, known for its busy metro station, market hall, and commercial activity.
-
E.
Balvanyos
Balvanyos is a Romanian mountain resort area known for its natural mineral springs, spa facilities, and scenic surroundings in the Eastern Carpathians.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00551521c8190b48d1a074bb4bdfc |
completed | April 15, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae274f6881908931569efc09996e |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3:05 a.m.