Triple
T7862723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma Ying-jeou |
E182537
|
entity |
| Predicate | startTime (Minister of Justice) |
P79434
|
FINISHED |
| Object | 1993-02-27 |
—
|
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: 1993-02-27 | Statement: [Ma Ying-jeou, startTime (Minister of Justice), 1993-02-27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTime (Minister of Justice) Context triple: [Ma Ying-jeou, startTime (Minister of Justice), 1993-02-27]
-
A.
startTime (Minister to the UK)
Indicates the date and time at which the person began serving in the role of Minister to the UK.
-
B.
startTime (as Attorney General)
Indicates the date and time at which an individual began serving in the role of Attorney General.
-
C.
officeStartTime (Minister of Justice of Italy)
Indicates the specific date and time at which an individual begins their term in office as Minister of Justice of Italy.
-
D.
startTime (Leader of the Labour Party)
Indicates the point in time at which someone began serving as Leader of the Labour Party.
-
E.
startTime (Chief Judge SDNY)
Indicates the specific time at which the tenure or role of the Chief Judge of the Southern District of New York begins.
- 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_69ca82887fd48190975896bf38c4596b |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb36be5f408190b82a097b0825c57a |
completed | March 31, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69cae925ca388190ae4a01fa76e957e8 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf786ec748190b6347b0c94335550 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:53 p.m.