Triple
T33758163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Todd Flanders |
E865032
|
entity |
| Predicate | frequentlySeenWith |
P111905
|
FINISHED |
| Object | Rod Flanders |
—
|
NE NERFINISHED |
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: Rod Flanders | Statement: [Todd Flanders, frequentlySeenWith, Rod Flanders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlySeenWith Context triple: [Todd Flanders, frequentlySeenWith, Rod Flanders]
-
A.
frequentlySeen
Indicates that one entity is observed or encountered many times or on a regular basis in relation to another entity.
-
B.
frequentlyUsedBy
Indicates that something is regularly or commonly utilized by a particular entity.
-
C.
commonlyLinkedTo
chosen
Indicates that one entity is frequently or typically associated, connected, or co-occurring with another entity.
-
D.
commonlyIdentifiedWith
Indicates that two entities are widely regarded or treated as the same or equivalent, even if they are formally distinct.
-
E.
oftenAccompaniedBy
Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with 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_69f3498d3b748190aa3c4006c1f32f38 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:45 a.m.