Triple
T10086281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberian general election, 2011 |
E215229
|
entity |
| Predicate | numberOfPresidentialRounds |
P91985
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Liberian general election, 2011, numberOfPresidentialRounds, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPresidentialRounds Context triple: [Liberian general election, 2011, numberOfPresidentialRounds, 2]
-
A.
numberOfPresidentialCampaigns
Indicates the total count of times an individual has run as a candidate in a presidential election.
-
B.
termCountAsPresident
Indicates the number of terms an individual has served in the role of president.
-
C.
numberOfTimesElectedGeneral
Indicates the number of times an entity has been elected to the position of general.
-
D.
presidentialVote
Indicates that an entity casts or records a vote in a presidential election for a particular candidate or option.
-
E.
numberOfTimesInOffice
Indicates the count of separate terms or periods an entity has held a particular office or position.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04745b48190a77c422eb76b6660 |
completed | April 2, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 9:01 p.m.