Triple
T20844774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karanganyar Regency |
E513191
|
entity |
| Predicate | hasTouristAttraction |
P530
|
FINISHED |
| Object |
Tawangmangu
Tawangmangu is a popular highland resort area in Central Java, Indonesia, known for its cool climate, scenic mountain landscapes, and the Grojogan Sewu waterfall.
|
E1453832
|
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: Tawangmangu | Statement: [Karanganyar Regency, hasTouristAttraction, Tawangmangu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tawangmangu Context triple: [Karanganyar Regency, hasTouristAttraction, Tawangmangu]
-
A.
Kertawangi
Kertawangi is a village located in West Bandung Regency in the West Java province of Indonesia.
-
B.
Manggar
Manggar is a coastal town on Belitung Island in Indonesia, known for its tin mining history and numerous traditional coffee shops.
-
C.
Kusno
Kusno was the birth name of Sukarno, the first President of Indonesia and a leading figure in the country’s independence movement.
-
D.
Nanggu
Nanggu is an Oceanic language spoken by a small community in the Solomon Islands, known for its distinct phonology and limited number of speakers.
-
E.
Sukawati
Sukawati is a district in Bali, Indonesia, known for its traditional art market, handicrafts, and cultural attractions within Gianyar Regency.
- 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: Tawangmangu Triple: [Karanganyar Regency, hasTouristAttraction, Tawangmangu]
Generated description
Tawangmangu is a popular highland resort area in Central Java, Indonesia, known for its cool climate, scenic mountain landscapes, and the Grojogan Sewu waterfall.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tawangmangu Target entity description: Tawangmangu is a popular highland resort area in Central Java, Indonesia, known for its cool climate, scenic mountain landscapes, and the Grojogan Sewu waterfall.
-
A.
Kertawangi
Kertawangi is a village located in West Bandung Regency in the West Java province of Indonesia.
-
B.
Manggar
Manggar is a coastal town on Belitung Island in Indonesia, known for its tin mining history and numerous traditional coffee shops.
-
C.
Kusno
Kusno was the birth name of Sukarno, the first President of Indonesia and a leading figure in the country’s independence movement.
-
D.
Nanggu
Nanggu is an Oceanic language spoken by a small community in the Solomon Islands, known for its distinct phonology and limited number of speakers.
-
E.
Sukawati
Sukawati is a district in Bali, Indonesia, known for its traditional art market, handicrafts, and cultural attractions within Gianyar Regency.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c34deef88190992b959b83bc59b1 |
completed | April 21, 2026, 12:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a090b01d11c8190a8ca8e331b2c0936 |
completed | May 17, 2026, 12:25 a.m. |
| NEDg | Description generation | batch_6a090bf30e048190a2c81dece02c997d |
completed | May 17, 2026, 12:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a090d0d52fc8190aed0a475f3424213 |
completed | May 17, 2026, 12:34 a.m. |
Created at: April 16, 2026, 12:43 p.m.