Triple
T28616416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GetTickCount |
E724282
|
entity |
| Predicate | timeOrigin |
P38044
|
FINISHED |
| Object | system startup |
—
|
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: system startup | Statement: [GetTickCount, timeOrigin, system startup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOrigin Context triple: [GetTickCount, timeOrigin, system startup]
-
A.
timePeriodOrigin
chosen
Indicates that one entity is the time period in which the other entity originated or first came into existence.
-
B.
timeSystem
Indicates a relationship where an entity uses, follows, or is defined within a particular system for measuring or organizing time.
-
C.
timeStartApprox
Indicates that the associated event or state begins at an approximate, rather than exact, point in time.
-
D.
timeZoneOffsetOrigin
Indicates the time difference between an entity’s local time and a defined origin or reference time zone.
-
E.
timeDomain
Indicates that something is characterized, defined, or analyzed with respect to time rather than another domain (such as frequency or space).
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 28, 2026, 4:32 a.m.