Triple
T21342516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Sam |
E526233
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Chau Doc |
—
|
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: Chau Doc | Statement: [Mount Sam, locatedIn, Chau Doc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chau Doc Context triple: [Mount Sam, locatedIn, Chau Doc]
-
A.
Chau Doc
chosen
Chau Doc is a riverfront city in Vietnam’s An Giang Province, known as a cultural crossroads near the Cambodian border and a gateway to the Mekong Delta.
-
B.
Long Xuyen
Long Xuyen is a major city in Vietnam’s Mekong Delta region, serving as the capital of An Giang Province and an important economic and cultural center.
-
C.
Lao Bảo
Lao Bảo is a border town in Quảng Trị Province, Vietnam, known as a key commercial and transit point on the route between Vietnam and Laos.
-
D.
Rach Gia
Rach Gia is a coastal city in Vietnam’s Kien Giang Province, known as a gateway to the Gulf of Thailand and nearby islands such as Phu Quoc.
-
E.
Tonquin
Tonquin was an early 19th-century American trading ship best known for its role in the Pacific Northwest fur trade and its disastrous expedition for John Jacob Astor’s Pacific Fur Company.
- 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_69e0b51c33048190ab27cede74ef798c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8a850617081909bf5c1ecc84d55b1 |
completed | April 22, 2026, 10:52 a.m. |
Created at: April 16, 2026, 4:44 p.m.