Triple
T23400649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Võ Văn Kiệt |
E559494
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Hanoi |
—
|
NE NERFINISHED |
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: Hanoi | Statement: [Võ Văn Kiệt, workLocation, Hanoi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanoi Context triple: [Võ Văn Kiệt, workLocation, Hanoi]
-
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.
Saigon
Saigon, now officially known as Ho Chi Minh City, is Vietnam’s largest city and a historic economic and cultural hub in the south of the country.
-
C.
Saigon
Saigon is an American rapper known for his socially conscious lyrics and work within the New York hip-hop scene.
-
D.
Hai Phong
Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
-
E.
Hanoi–Ho Chi Minh City
Hanoi–Ho Chi Minh City is Vietnam’s busiest and most important domestic air route, linking the nation’s capital in the north with its largest economic hub in the south.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4dfa4c881908df0eced4855c0d9 |
completed | April 29, 2026, 6:27 a.m. |
Created at: April 17, 2026, 5:37 p.m.