Triple
T23313877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zagorje |
E590651
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Stubičke Toplice
Stubičke Toplice is a Croatian spa town in the Zagorje region, known for its thermal springs and health tourism.
|
E1579446
|
NE FINISHED |
How this triple was built (4 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: Stubičke Toplice | Statement: [Zagorje, hasSettlement, Stubičke Toplice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stubičke Toplice Context triple: [Zagorje, hasSettlement, Stubičke Toplice]
-
A.
Topčider
Topčider is a historic park and neighborhood in Belgrade, Serbia, known for its royal residence, lush greenery, and cultural significance.
-
B.
Topoloveni
Topoloveni is a small town in southern Romania known for its traditional plum jam and location in the historical region of Muntenia.
-
C.
Vranjska Banja
Vranjska Banja is a Serbian spa town renowned for its thermal mineral springs and health tourism facilities in the southern part of the country.
-
D.
Vrnjačka Banja
Vrnjačka Banja is a renowned Serbian spa town famous for its mineral springs, wellness tourism, and picturesque parks.
-
E.
Niška Banja
Niška Banja is a well-known Serbian spa town near Niš, recognized for its thermal mineral springs and health tourism facilities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Stubičke Toplice Triple: [Zagorje, hasSettlement, Stubičke Toplice]
Generated description
Stubičke Toplice is a Croatian spa town in the Zagorje region, known for its thermal springs and health tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stubičke Toplice Target entity description: Stubičke Toplice is a Croatian spa town in the Zagorje region, known for its thermal springs and health tourism.
-
A.
Topčider
Topčider is a historic park and neighborhood in Belgrade, Serbia, known for its royal residence, lush greenery, and cultural significance.
-
B.
Topoloveni
Topoloveni is a small town in southern Romania known for its traditional plum jam and location in the historical region of Muntenia.
-
C.
Vranjska Banja
Vranjska Banja is a Serbian spa town renowned for its thermal mineral springs and health tourism facilities in the southern part of the country.
-
D.
Vrnjačka Banja
Vrnjačka Banja is a renowned Serbian spa town famous for its mineral springs, wellness tourism, and picturesque parks.
-
E.
Niška Banja
Niška Banja is a well-known Serbian spa town near Niš, recognized for its thermal mineral springs and health tourism facilities.
- F. None of above. chosen
Provenance (5 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_69e25d1d32188190948eb76909d1dcc3 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1977ee5d08190a9519d7867d6bef9 |
completed | April 29, 2026, 5:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c4ca2fb888190931e944c3df87188 |
completed | May 19, 2026, 11:42 a.m. |
| NEDg | Description generation | batch_6a0c4e669b6481909f198d1c51b68bf3 |
completed | May 19, 2026, 11:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c4f011a188190b801f2ae0f134356 |
completed | May 19, 2026, 11:52 a.m. |
Created at: April 17, 2026, 5:06 p.m.