Triple
T10778029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodluck Jonathan administration in Nigeria |
E254245
|
entity |
| Predicate | tookOfficeAsActingPresident |
P84636
|
FINISHED |
| Object | February 2010 |
—
|
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: February 2010 | Statement: [Goodluck Jonathan administration in Nigeria, tookOfficeAsActingPresident, February 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookOfficeAsActingPresident Context triple: [Goodluck Jonathan administration in Nigeria, tookOfficeAsActingPresident, February 2010]
-
A.
assumedOfficeAsInterimPresident
Indicates that an individual temporarily took on the role and responsibilities of president in an interim capacity.
-
B.
termAsActingPresidentStart
chosen
Indicates the date or point in time when an individual begins serving in the role of acting president.
-
C.
endTimeAsInterimPresident
Indicates the point in time at which an individual's tenure serving as interim president concludes.
-
D.
triggerForInterimPresidency
Indicates that an event or condition serves as the cause or activating factor that initiates an interim presidency.
-
E.
servedAsPresidentDuring
Indicates that a person held the office of president for the duration of a specified time period or event.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732c18c3c819089d49e3e4585049e |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.