Triple
T21449083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bee Vang |
E529158
|
entity |
| Predicate | portrayed |
P1668
|
FINISHED |
| Object | Thao Vang Lor |
E1485549
|
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: Thao Vang Lor | Statement: [Bee Vang, portrayed, Thao Vang Lor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thao Vang Lor Context triple: [Bee Vang, portrayed, Thao Vang Lor]
-
A.
Thao Vang Lor
chosen
Thao Vang Lor is a shy Hmong American teenager who becomes the reluctant protégé of his gruff neighbor Walt Kowalski in the film "Gran Torino."
-
B.
Thavung
Thavung is an ethnic minority group in Vietnam, culturally and linguistically distinct yet historically connected to the majority Kinh people.
-
C.
Tongzha Hlai
Tongzha Hlai is a specific variety of the Hlai language cluster spoken by the Hlai people on Hainan Island in southern China.
-
D.
Duong Dong
Duong Dong is the main town and commercial center of Phu Quoc Island in Vietnam, known for its bustling markets, beaches, and role as the island’s primary hub for tourism and services.
-
E.
Senh Duong
Senh Duong is an entrepreneur and web developer best known as the creator of the influential film and television review aggregation website Rotten Tomatoes.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d11ca48190aafe25c97dfa5578 |
completed | April 23, 2026, 9:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09cfe9f264819085b05974b8782c4d |
completed | May 17, 2026, 2:25 p.m. |
Created at: April 16, 2026, 6:06 p.m.