Triple
T54143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Internet Engineering Task Force |
E1066
|
entity |
| Predicate | meetingFrequency |
P2557
|
FINISHED |
| Object | three times per year |
—
|
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: three times per year | Statement: [Internet Engineering Task Force, meetingFrequency, three times per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetingFrequency Context triple: [Internet Engineering Task Force, meetingFrequency, three times per year]
-
A.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
B.
appointmentMethod
Indicates how an appointment is arranged, such as the channel, process, or means used to schedule it.
-
C.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
D.
convenes
Indicates bringing people or groups together to formally meet, discuss, or deliberate on a particular matter.
-
E.
awardedFrequency
Indicates how often an award or recognition is given within a specified time 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b3a9e848190b80de3c858678b3a |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ac52fb08190aa7c38f83434f795 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b39eef081909cec4333f2b25513 |
completed | Feb. 28, 2026, 1:56 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.