Triple
T371767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southeast Asia |
E8284
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Java Sea |
E23517
|
NE FINISHED |
How this triple was built (2 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: Java Sea | Statement: [Southeast Asia, borderedBy, Java Sea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Java Sea Context triple: [Southeast Asia, borderedBy, Java Sea]
-
A.
Java Sea
chosen
The Java Sea is a shallow, tropical marginal sea in Indonesia, lying between the islands of Java and Borneo and known for its busy shipping routes and rich marine biodiversity.
-
B.
Bluewater
Bluewater is a large out-of-town shopping and leisure centre located in Kent, England.
-
C.
Java
Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
-
D.
Java
Java is a widely used, object-oriented programming language known for its platform independence and extensive use in enterprise, web, and mobile application development.
-
E.
Spui
Spui is a central square and tram hub in Amsterdam, Netherlands, known for its bookstores, cultural venues, and proximity to historic canals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec00785481908551fc3571fcca47 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f0a78c748190ae5e64919f1d6501 |
completed | March 1, 2026, 7:54 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.