Triple
T33578651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seiberg–Witten differential |
E860093
|
entity |
| Predicate | hasPeriods |
P195003
|
FINISHED |
| Object | electric periods |
—
|
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: electric periods | Statement: [Seiberg–Witten differential, hasPeriods, electric periods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPeriods Context triple: [Seiberg–Witten differential, hasPeriods, electric periods]
-
A.
hasPeriodOf
Indicates that one entity possesses, experiences, or is associated with a specific span or interval of time.
-
B.
hasPeriodRange
Indicates that there is a temporal span or interval during which something is valid, active, or applicable.
-
C.
hasPeriodTitles
Indicates that an entity is associated with one or more titles that apply specifically to a defined time period.
-
D.
includesPeriodFeature
Indicates that something contains or incorporates a specific period-related feature as part of its characteristics or structure.
-
E.
hasPeriodLength
Indicates that something is associated with a specific duration or length of a recurring cycle or period.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69fd974c0e8481909fdd312897c647b3 |
completed | May 8, 2026, 7:57 a.m. |
Created at: May 1, 2026, 1:40 a.m.