Triple
T2624710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honorary Doctorate from Yale University |
E59088
|
entity |
| Predicate | typicalConferralFrequency |
P2205
|
FINISHED |
| Object | annually |
—
|
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: annually | Statement: [Honorary Doctorate from Yale University, typicalConferralFrequency, annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalConferralFrequency Context triple: [Honorary Doctorate from Yale University, typicalConferralFrequency, annually]
-
A.
awardedFrequency
chosen
Indicates how often an award or recognition is given within a specified time period.
-
B.
typicalFrequencyUnit
Indicates the unit of measurement typically used to express the frequency of an event, action, or occurrence.
-
C.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
D.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
E.
laterFrequency
Indicates that one event, state, or action occurs with a lower frequency than another in a temporal sequence.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdaca581881908fe8d3d820f839b7 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd80f48888190afdf7e3e042157d0 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.