Triple
T7588434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yìxiān |
E179673
|
entity |
| Predicate | bearerMajorRole |
P14496
|
FINISHED |
| Object | provisional first president of the Republic of China |
—
|
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: provisional first president of the Republic of China | Statement: [Yìxiān, bearerMajorRole, provisional first president of the Republic of China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerMajorRole Context triple: [Yìxiān, bearerMajorRole, provisional first president of the Republic of China]
-
A.
peakRole
Indicates the role or position an entity holds at the highest or most prominent point of its activity, status, or performance.
-
B.
laterPrimaryRole
Indicates that an entity assumes a specified primary role at a later time than another role or state in a sequence.
-
C.
canonicalRole
Indicates that an entity holds a standard, primary, or officially recognized role within a particular context or system.
-
D.
hasMainRole
chosen
Indicates that an entity holds the primary or most significant role in relation to another entity or context.
-
E.
encodingRole
Indicates the role or function an entity has in the process of encoding information into a particular form or representation.
- 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_69c69f335248819093c1006f30513708 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f99875908190b09584cf13ea1e08 |
completed | March 27, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:52 p.m.