Triple
T2390260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chao Phraya River |
E48923
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object | Port of Bangkok |
E195427
|
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: Port of Bangkok | Statement: [Chao Phraya River, hasPort, Port of Bangkok]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Port of Bangkok Context triple: [Chao Phraya River, hasPort, Port of Bangkok]
-
A.
Bangkok Port
chosen
Bangkok Port is a major seaport and logistics hub serving Thailand’s capital city and central region.
-
B.
Port of Singapore
The Port of Singapore is one of the world’s busiest and most important maritime hubs, serving as a major global transshipment and logistics center.
-
C.
Port of Yangon
The Port of Yangon is Myanmar’s principal seaport and trade gateway, handling the majority of the country’s maritime cargo and connecting it to regional and global shipping routes.
-
D.
Laem Chabang
Laem Chabang is Thailand’s largest deep-sea commercial port and a major hub for maritime trade in Southeast Asia.
-
E.
Hat Yai
Hat Yai is a major commercial and transportation hub city in southern Thailand, known for its bustling markets and proximity to the Malaysian border.
- 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_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc7de1478819082238e8b8f88ed06 |
completed | March 7, 2026, 6:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3d4f0608190bcc77a67fa85b963 |
completed | March 9, 2026, 11:49 a.m. |
Created at: March 4, 2026, 7:57 p.m.