Triple
T7756050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City mayoral elections |
E175897
|
entity |
| Predicate | typicalElectionMonth |
P78534
|
FINISHED |
| Object | November |
—
|
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: November | Statement: [New York City mayoral elections, typicalElectionMonth, November]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalElectionMonth Context triple: [New York City mayoral elections, typicalElectionMonth, November]
-
A.
generalElectionMonth
Indicates the month during which a general election is scheduled to occur or took place.
-
B.
typicalBroadcastMonth
Indicates the month in which something is most commonly or characteristically broadcast.
-
C.
electionDate
Indicates the specific calendar date on which an election is scheduled to be or was held.
-
D.
typicalMeetingMonth
Indicates the month in which an entity most commonly or usually holds its meetings.
-
E.
electionsScheduledFor
Indicates that a specific election is planned or set to occur at a particular time or for a particular entity.
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c705257ca08190a78c592a1e616da8 |
completed | March 27, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69c7016df2b08190b2330a2010691431 |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c70524c3948190a163dc5f4ecdffa7 |
completed | March 27, 2026, 10:31 p.m. |
Created at: March 27, 2026, 4:08 p.m.