Triple
T1498776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the Republic of China |
E29746
|
entity |
| Predicate | style |
P87
|
FINISHED |
| Object | Madam President |
E1667
|
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: Madam President | Statement: [President of the Republic of China, style, Madam President]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madam President Context triple: [President of the Republic of China, style, Madam President]
-
A.
Madam President
chosen
"Madam President" is the formal style of address used for a female President of the United States.
-
B.
Madam Vice President
"Madam Vice President" is the formal mode of address used for a woman serving as Vice President of the United States.
-
C.
Madam Speaker
"Madam Speaker" is the formal mode of address used for a woman serving as Speaker of the United States House of Representatives.
-
D.
Mr. President
"Mr. President" is the formal style of address used for the presiding officer of the Massachusetts Senate.
-
E.
Mr. President
"Mr. President" is a formal style of address used for the President of Ecuador.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6f0ce988190aafab4a6e0dfd710 |
completed | March 1, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad2331b49881908672251bb86418df |
completed | March 8, 2026, 7:20 a.m. |
Created at: March 1, 2026, 8:12 p.m.