Triple
T7195938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malang Regency |
E168614
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Kepanjen
Kepanjen is a town in East Java, Indonesia, known as an administrative and growing urban center within the Malang region.
|
E654738
|
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: Kepanjen | Statement: [Malang Regency, capital, Kepanjen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kepanjen Context triple: [Malang Regency, capital, Kepanjen]
-
A.
Nganjuk
Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
-
B.
Citeureup
Citeureup is a district in West Java, Indonesia, known as one of the industrial and residential areas within the Bogor metropolitan region.
-
C.
Trenggalek
Trenggalek is a regency and its capital town in southern East Java, Indonesia, known for its coastal landscapes, caves, and agricultural economy.
-
D.
Pasuruan
Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
-
E.
Tulungagung
Tulungagung is a regency and urban center in southern East Java, Indonesia, known for its marble industry and coastal landscapes along the Indian Ocean.
- 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: Kepanjen Triple: [Malang Regency, capital, Kepanjen]
Generated description
Kepanjen is a town in East Java, Indonesia, known as an administrative and growing urban center within the Malang region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kepanjen Target entity description: Kepanjen is a town in East Java, Indonesia, known as an administrative and growing urban center within the Malang region.
-
A.
Nganjuk
Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
-
B.
Citeureup
Citeureup is a district in West Java, Indonesia, known as one of the industrial and residential areas within the Bogor metropolitan region.
-
C.
Trenggalek
Trenggalek is a regency and its capital town in southern East Java, Indonesia, known for its coastal landscapes, caves, and agricultural economy.
-
D.
Pasuruan
Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
-
E.
Tulungagung
Tulungagung is a regency and urban center in southern East Java, Indonesia, known for its marble industry and coastal landscapes along the Indian Ocean.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e927709c81909edf6ee42fe7f833 |
completed | March 27, 2026, 8:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e516e3708190b4025e1a5e22d537 |
completed | March 28, 2026, 2:26 p.m. |
| NEDg | Description generation | batch_69c7e64cdce48190884b3c5e2ceaf60e |
completed | March 28, 2026, 2:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7e6ac5dd08190bb84259cbb44cba9 |
completed | March 28, 2026, 2:33 p.m. |
Created at: March 27, 2026, 2:51 p.m.