Triple
T1533996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vietnam Airlines |
E32508
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
VASCO
VASCO is a regional airline in Vietnam that operates domestic flights, often serving smaller airports and routes on behalf of Vietnam Airlines.
|
E174883
|
NE FINISHED |
How this triple was built (4 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: VASCO | Statement: [Vietnam Airlines, hasSubsidiary, VASCO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VASCO Context triple: [Vietnam Airlines, hasSubsidiary, VASCO]
-
A.
Vivanco
Vivanco is a Spanish-language surname of likely Iberian origin borne by various notable individuals.
-
B.
Vuse
Vuse is an electronic cigarette and vaping product brand owned by British American Tobacco, known for its range of nicotine e-liquids and devices.
-
C.
Magalhães Network
Magalhães Network is an academic consortium that promotes cooperation, mobility, and exchange programs among universities in Ibero-America and Europe, particularly in engineering and related fields.
-
D.
Porvenir
Porvenir is a small Chilean town on Tierra del Fuego that serves as an important fishing and service port on the Strait of Magellan.
-
E.
Porvenir
Porvenir is a small town that serves as the capital of Pando Department in northern Bolivia, near the border with Brazil.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: VASCO Triple: [Vietnam Airlines, hasSubsidiary, VASCO]
Generated description
VASCO is a regional airline in Vietnam that operates domestic flights, often serving smaller airports and routes on behalf of Vietnam Airlines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VASCO Target entity description: VASCO is a regional airline in Vietnam that operates domestic flights, often serving smaller airports and routes on behalf of Vietnam Airlines.
-
A.
Vivanco
Vivanco is a Spanish-language surname of likely Iberian origin borne by various notable individuals.
-
B.
Vuse
Vuse is an electronic cigarette and vaping product brand owned by British American Tobacco, known for its range of nicotine e-liquids and devices.
-
C.
Magalhães Network
Magalhães Network is an academic consortium that promotes cooperation, mobility, and exchange programs among universities in Ibero-America and Europe, particularly in engineering and related fields.
-
D.
Porvenir
Porvenir is a small Chilean town on Tierra del Fuego that serves as an important fishing and service port on the Strait of Magellan.
-
E.
Porvenir
Porvenir is a small town that serves as the capital of Pando Department in northern Bolivia, near the border with Brazil.
- F. None of above. chosen
Provenance (5 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa61f8df00819086f34847e2170e12 |
completed | March 6, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad295a03d881909071fb437c2d19ba |
completed | March 8, 2026, 7:46 a.m. |
| NEDg | Description generation | batch_69ad2a1957e481908b07d3f4df75fbfe |
completed | March 8, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad2b2929348190ac35ff8d405894d6 |
completed | March 8, 2026, 7:54 a.m. |
Created at: March 4, 2026, 7:26 p.m.