Triple
T15103383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budapest Metro Line 4 |
E360724
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Rákóczi tér |
E1087995
|
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: Rákóczi tér | Statement: [Budapest Metro Line 4, hasStation, Rákóczi tér]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rákóczi tér Context triple: [Budapest Metro Line 4, hasStation, Rákóczi tér]
-
A.
Rákóczi tér
chosen
Rákóczi tér is a public square and transport hub in Budapest known for its central location and metro station in the Józsefváros district.
-
B.
Vörösmarty tér
Vörösmarty tér is a prominent central square in Budapest, Hungary, known for its historic cafés, shopping streets, and seasonal markets.
-
C.
Nagyvárad tér
Nagyvárad tér is a metro station in Budapest that serves the city’s public transportation network on one of its main lines.
-
D.
Erzsébet tér
Erzsébet tér is a central square and popular public park in downtown Budapest, known for its green spaces, cultural venues, and vibrant urban atmosphere.
-
E.
Széchenyi István tér
Széchenyi István tér is a prominent square in central Budapest, Hungary, known for its grand riverside location by the Danube and its surrounding historic and cultural landmarks.
- 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_69ff6ec2f35c8190a96af080cd7b6d0e |
completed | May 9, 2026, 5:28 p.m. |
Created at: April 10, 2026, 3:05 a.m.