Triple
T9738277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngô Viết Thụ |
E236120
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ngô |
E125405
|
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: Ngô | Statement: [Ngô Viết Thụ, familyName, Ngô]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ngô Context triple: [Ngô Viết Thụ, familyName, Ngô]
-
A.
Ngo
chosen
Ngo is a Vietnamese surname most prominently associated with figures such as former South Vietnamese president Ngo Dinh Diem.
-
B.
Thieu
Thieu is the family name of Nguyen Van Thieu, the South Vietnamese general and president during the Vietnam War.
-
C.
Guan
Guan is a common Chinese surname with historical roots and multiple romanized variants, including Kwan.
-
D.
Suo-Gân
Suo-Gân is a traditional Welsh lullaby known for its gentle melody and soothing, lyrical character.
-
E.
Hoan
Hoan is a surname most notably associated with Daniel Hoan, a long-serving Socialist mayor of Milwaukee in the early 20th century.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9ef2ba048190811d6f4251fdb270 |
completed | April 1, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1afe0dab48190832ab77265c09d70 |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:22 p.m.