Triple
T1366176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Java |
E30008
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Tuban
Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
|
E201811
|
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: Tuban | Statement: [East Java, hasMajorCity, Tuban]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tuban Context triple: [East Java, hasMajorCity, Tuban]
-
A.
Blitar
Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
-
B.
Tabanan Regency
Tabanan Regency is an agricultural and coastal region in western Bali, Indonesia, known for its lush rice terraces and the iconic Tanah Lot sea temple.
-
C.
Mojokerto
Mojokerto is a city in Indonesia known for its historical significance as part of the former Majapahit Empire and its location in the province of East Java.
-
D.
Gresik
Gresik is an industrial and port city in Indonesia known for its cement production and role as part of the Surabaya metropolitan area.
-
E.
Pasuruan
Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
- 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: Tuban Triple: [East Java, hasMajorCity, Tuban]
Generated description
Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tuban Target entity description: Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
-
A.
Blitar
Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
-
B.
Tabanan Regency
Tabanan Regency is an agricultural and coastal region in western Bali, Indonesia, known for its lush rice terraces and the iconic Tanah Lot sea temple.
-
C.
Mojokerto
Mojokerto is a city in Indonesia known for its historical significance as part of the former Majapahit Empire and its location in the province of East Java.
-
D.
Gresik
Gresik is an industrial and port city in Indonesia known for its cement production and role as part of the Surabaya metropolitan area.
-
E.
Pasuruan
Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d1d15481909d58b6fd8aa2e585 |
completed | March 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5af961c8190aed3129dab0fecf3 |
completed | March 8, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69adb8b2b01c8190997179cdfd55da13 |
completed | March 8, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb94aaf348190a28ca8e9d9cacf41 |
completed | March 8, 2026, 6 p.m. |
Created at: March 1, 2026, 7:57 p.m.