Triple
T301502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor-General of French Indochina |
E6205
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Saigon |
E6450
|
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: Saigon | Statement: [Governor-General of French Indochina, seat, Saigon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saigon Context triple: [Governor-General of French Indochina, seat, Saigon]
-
A.
Saigon
chosen
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.
-
B.
Hanoi
Hanoi is the historic and modern capital of Vietnam, known for its centuries-old architecture, rich cultural heritage, and vibrant street life.
-
C.
Hai Phong
Hai Phong is a major port city in northern Vietnam known for its industrial economy and coastal location.
-
D.
Da Nang
Da Nang is a major coastal city in central Vietnam known for its sandy beaches, modern infrastructure, and proximity to historic sites like Hoi An and the Marble Mountains.
-
E.
Bangkok
Bangkok is the vibrant capital and largest city of Thailand, known for its bustling street life, ornate temples, and role as a major economic and cultural hub in Southeast Asia.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e9e6a8308190b9bd15310e324504 |
completed | Feb. 28, 2026, 1:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3c4141d288190a6873cf20e360fe1 |
completed | March 1, 2026, 4:44 a.m. |
Created at: Feb. 28, 2026, 1:06 p.m.