Triple
T19738594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Rydell |
E474052
|
entity |
| Predicate | oftenDiscusses |
P55019
|
FINISHED |
| Object | social issues |
—
|
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: social issues | Statement: [Dan Rydell, oftenDiscusses, social issues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenDiscusses Context triple: [Dan Rydell, oftenDiscusses, social issues]
-
A.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
B.
oftenSays
chosen
Indicates that one entity frequently makes a particular statement or remark, or regularly expresses a certain idea or phrase.
-
C.
canDiscuss
Indicates that one entity is able or permitted to engage in a discussion or conversation with another entity.
-
D.
oftenHave
Indicates that one entity frequently possesses, experiences, or is associated with another entity.
-
E.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6515f6efc8190a3da113847464399 |
completed | April 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.