Triple
T2190916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Jackson presidential election |
E49857
|
entity |
| Predicate | hasRegionOfStrongSupportForWinner |
P31408
|
FINISHED |
| Object | South |
—
|
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: South | Statement: [Andrew Jackson presidential election, hasRegionOfStrongSupportForWinner, South]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionOfStrongSupportForWinner Context triple: [Andrew Jackson presidential election, hasRegionOfStrongSupportForWinner, South]
-
A.
strongestSupportRegion
chosen
Indicates the region where an entity receives its highest level of support compared to all other regions.
-
B.
winnerRepresents
Indicates that the winner of a competition or contest serves as a representative for a particular group, organization, or entity.
-
C.
wonFor
Indicates that one entity received an award, prize, or recognition specifically on behalf of or representing another entity.
-
D.
popularVoteWinner
Indicates that the subject is the candidate who received the highest number of individual votes cast by the electorate in an election.
-
E.
electoralSuccess
Indicates that an entity has achieved a favorable or winning outcome in an election or electoral process.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf3f5e008190beda3ce5d77209e0 |
completed | March 7, 2026, 6:01 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.