Triple
T21149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electoral College |
E419
|
entity |
| Predicate | firstUsedInElection |
P1624
|
FINISHED |
| Object | 1789 |
—
|
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: 1789 | Statement: [Electoral College, firstUsedInElection, 1789]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstUsedInElection Context triple: [Electoral College, firstUsedInElection, 1789]
-
A.
firstInOfficeTo
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another entity or context.
-
B.
firstCelebratedInYear
Indicates the year in which something (such as an event, holiday, or celebration) was first observed or celebrated.
-
C.
electedCandidate
Indicates that a particular person has been chosen as the winner in an election for a given position or office.
-
D.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
E.
electionNumber
Indicates the specific ordinal or identifying number assigned to a particular election within a series or system of elections.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246f7bd30819085f751c41f6f029e |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246526f5881909bc2a46e978bd082 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246f4d7908190a947f6da251c6f3b |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.