Triple
T8516811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hai Ba Trung District |
E201591
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Vinh Tuy Ward
Vinh Tuy Ward is an urban administrative subdivision of Hanoi, Vietnam, located within the central Hai Bà Trưng District.
|
E738922
|
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: Vinh Tuy Ward | Statement: [Hai Ba Trung District, contains, Vinh Tuy Ward]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vinh Tuy Ward Context triple: [Hai Ba Trung District, contains, Vinh Tuy Ward]
-
A.
Ben Thanh Ward
Ben Thanh Ward is a central urban neighborhood in Ho Chi Minh City, Vietnam, known for its bustling commercial activity and proximity to the iconic Ben Thanh Market.
-
B.
Nghia Tan Ward
Nghia Tan Ward is an urban residential and commercial neighborhood located within Hanoi’s Cầu Giấy District in Vietnam.
-
C.
Xuan Truong
Xuan Truong is a township in Nam Định Province, Vietnam, serving as the administrative and economic center of Xuan Truong District.
-
D.
Tung Thanh Tran
Tung Thanh Tran is an actor best known for his role in the 1987 war-comedy film "Good Morning, Vietnam."
-
E.
Quyen Tran
Quyen Tran is an American cinematographer known for her visually expressive work on independent films and character-driven stories.
- 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: Vinh Tuy Ward Triple: [Hai Ba Trung District, contains, Vinh Tuy Ward]
Generated description
Vinh Tuy Ward is an urban administrative subdivision of Hanoi, Vietnam, located within the central Hai Bà Trưng District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vinh Tuy Ward Target entity description: Vinh Tuy Ward is an urban administrative subdivision of Hanoi, Vietnam, located within the central Hai Bà Trưng District.
-
A.
Ben Thanh Ward
Ben Thanh Ward is a central urban neighborhood in Ho Chi Minh City, Vietnam, known for its bustling commercial activity and proximity to the iconic Ben Thanh Market.
-
B.
Nghia Tan Ward
Nghia Tan Ward is an urban residential and commercial neighborhood located within Hanoi’s Cầu Giấy District in Vietnam.
-
C.
Xuan Truong
Xuan Truong is a township in Nam Định Province, Vietnam, serving as the administrative and economic center of Xuan Truong District.
-
D.
Tung Thanh Tran
Tung Thanh Tran is an actor best known for his role in the 1987 war-comedy film "Good Morning, Vietnam."
-
E.
Quyen Tran
Quyen Tran is an American cinematographer known for her visually expressive work on independent films and character-driven stories.
- 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62550908190af882019d68a904a |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e65419481909e787066fd069565 |
completed | April 2, 2026, 11:09 a.m. |
| NEDg | Description generation | batch_69ce4ffac8a08190bc2131c0d260ca39 |
completed | April 2, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce5117c7508190b74821d029d226c6 |
completed | April 2, 2026, 11:20 a.m. |
Created at: March 30, 2026, 6:15 p.m.