Triple
T1938939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khmer script |
E41507
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | Vietnam |
E4138
|
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: Vietnam | Statement: [Khmer script, usedIn, Vietnam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vietnam Context triple: [Khmer script, usedIn, Vietnam]
-
A.
Viet Nam
chosen
Viet Nam is a Southeast Asian nation known for its rapid economic growth, rich cultural heritage, and strategic role in regional and global trade.
-
B.
Democratic Republic of Vietnam
The Democratic Republic of Vietnam was the communist state in northern Vietnam that led the struggle against the United States and South Vietnam during the Vietnam War and later unified the country under its rule.
-
C.
Viet
Viet refers to the ethnic Vietnamese people, the majority ethnic group of Vietnam with a distinct language and culture.
-
D.
Cochinchina
Cochinchina was the southern region of Vietnam that became a French colony and later formed part of French Indochina.
-
E.
Laos
Laos is a landlocked Southeast Asian country known for its mountainous terrain, Buddhist culture, and status as one of the region’s least developed but rapidly reforming economies.
- 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2c8be648190836580cec77a143f |
completed | March 7, 2026, 5:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fae5aa08190b6aa50b543a175b8 |
completed | March 9, 2026, 1:17 a.m. |
Created at: March 4, 2026, 7:36 p.m.