Triple
T1764558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secretary of the Hanoi Party Committee |
E38731
|
entity |
| Predicate | titleInVietnamese |
P31478
|
FINISHED |
| Object | Bí thư Thành ủy Hà Nội |
—
|
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: Bí thư Thành ủy Hà Nội | Statement: [Secretary of the Hanoi Party Committee, titleInVietnamese, Bí thư Thành ủy Hà Nội]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleInVietnamese Context triple: [Secretary of the Hanoi Party Committee, titleInVietnamese, Bí thư Thành ủy Hà Nội]
-
A.
titleInJapanese
Indicates that one entity is the title of another entity expressed specifically in the Japanese language.
-
B.
titleInEnglish
Indicates that an entity’s title or name is given in the English language.
-
C.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
D.
titleVariant
Indicates that one title is an alternative or variant form of another title referring to the same work or entity.
-
E.
titles
Indicates that one entity holds a formal title, designation, or name associated with another entity.
- F. None of above. chosen
Provenance (4 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab173936b4819097332ee185996bbd |
completed | March 6, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69aa61c9e06c819085489e00cfe72153 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab173830a481908b67928f16f5d999 |
completed | March 6, 2026, 6:04 p.m. |
Created at: March 4, 2026, 7:31 p.m.