Triple
T1694662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indonesian archipelago |
E36629
|
entity |
| Predicate | hasMajorIsland |
P756
|
FINISHED |
| Object |
Bangka
Bangka is a large Indonesian island off the east coast of Sumatra, known for its tin mining and beautiful beaches.
|
E192623
|
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: Bangka | Statement: [Indonesian archipelago, hasMajorIsland, Bangka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bangka Context triple: [Indonesian archipelago, hasMajorIsland, Bangka]
-
A.
Bantia
Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
-
B.
Kainan
Kainan is a coastal city in central Wakayama Prefecture, Japan, known for its traditional industries and scenic seaside setting.
-
C.
Labuan
Labuan is a federal territory of Malaysia comprising a main island and several smaller ones, known as an offshore financial center and duty-free port off the coast of Borneo.
-
D.
Labuan
Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
-
E.
Banjar
Banjar is a city in the eastern part of West Java, Indonesia, known as a regional transit hub connecting West Java with Central Java.
- 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: Bangka Triple: [Indonesian archipelago, hasMajorIsland, Bangka]
Generated description
Bangka is a large Indonesian island off the east coast of Sumatra, known for its tin mining and beautiful beaches.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bangka Target entity description: Bangka is a large Indonesian island off the east coast of Sumatra, known for its tin mining and beautiful beaches.
-
A.
Bantia
Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
-
B.
Kainan
Kainan is a coastal city in central Wakayama Prefecture, Japan, known for its traditional industries and scenic seaside setting.
-
C.
Labuan
Labuan is a federal territory of Malaysia comprising a main island and several smaller ones, known as an offshore financial center and duty-free port off the coast of Borneo.
-
D.
Labuan
Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
-
E.
Banjar
Banjar is a city in the eastern part of West Java, Indonesia, known as a regional transit hub connecting West Java with Central Java.
- 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62b3b8908190afc3f9e4a384684f |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ac9ed2c81909fe3fe40515526de |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad9575acf88190aa3fe80794534dd4 |
completed | March 8, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad97a7128c819097ff36216f00d4f9 |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 4, 2026, 7:29 p.m.