Triple
T30447932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tổng Khởi Nghĩa Tháng Tám |
E774631
|
entity |
| Predicate | đốiTượngĐấuTranh |
P18835
|
FINISHED |
| Object | chính quyền thực dân Pháp ở Đông Dương |
—
|
LITERAL 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: chính quyền thực dân Pháp ở Đông Dương | Statement: [Tổng Khởi Nghĩa Tháng Tám, đốiTượngĐấuTranh, chính quyền thực dân Pháp ở Đông Dương]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: đốiTượngĐấuTranh Context triple: [Tổng Khởi Nghĩa Tháng Tám, đốiTượngĐấuTranh, chính quyền thực dân Pháp ở Đông Dương]
-
A.
واجه
Indicates that one entity confronts, faces, or encounters another entity or situation, often involving direct opposition or challenge.
-
B.
diesFighting
Indicates that an entity dies as a direct result of engaging in a fight or combat.
-
C.
typeOfDuel
Indicates the specific kind or category of duel that characterizes a given dueling event or relationship between opponents.
-
D.
epicBattle
Indicates a large-scale, intense conflict or confrontation between opposing entities, often marked by extraordinary stakes or dramatic significance.
-
E.
battleOpponent
chosen
Indicates that two entities are engaged in or designated as opponents in a battle or combat scenario.
- F. None of above.
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_69f22493ef9c8190ae8c2afcb7f994c8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f686c07ac48190b5169557e67861c9 |
completed | May 2, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:09 p.m.