Triple
T15183580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sông Hồng |
E362809
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Hà Nội |
E6204
|
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: Hà Nội | Statement: [Sông Hồng, passesThrough, Hà Nội]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hà Nội Context triple: [Sông Hồng, passesThrough, Hà Nội]
-
A.
Hanoi
chosen
Hanoi is the historic and modern capital of Vietnam, known for its centuries-old architecture, rich cultural heritage, and vibrant street life.
-
B.
Hà Nội Municipality
Hà Nội Municipality is the capital-level administrative unit of Vietnam, encompassing the historic city of Hanoi and its surrounding districts as a major political, economic, and cultural center.
-
C.
Hai Phong
Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
-
D.
Pekin
Pekin is a small hamlet in Niagara County, New York, known historically as a stop on the Underground Railroad.
-
E.
Hanoi Capital Region
The Hanoi Capital Region is a key metropolitan and administrative area in northern Vietnam centered on Hanoi, serving as the country’s political hub and a major economic and cultural center.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006663ad48190986b680001be0e9b |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed32e425c819083f10f947c258a9b |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 3:09 a.m.