Triple
T163259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States presidential election |
E2955
|
entity |
| Predicate | occursInMonth |
P1167
|
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: [United States presidential election, occursInMonth, November]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occursInMonth Context triple: [United States presidential election, occursInMonth, November]
-
A.
monthObserved
chosen
Indicates the month during which an event, observation, or measurement took place.
-
B.
meetsEvery
Indicates that one entity encounters or comes into contact with every member of a specified set of entities.
-
C.
occurredDuring
Indicates that one event or action took place within the temporal span of another event or time period.
-
D.
dateDetermination
Indicates the process or criteria by which a specific date is identified, calculated, or assigned in relation to an event or condition.
-
E.
dateObserved
Indicates the specific date on which an event, condition, or measurement was recorded or observed.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a2585a1a6481908899ad51211950e8 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2566392208190a538ea9aa1fac53e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.