Triple
T33995335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pep Streebek |
E871656
|
entity |
| Predicate | relationshipToJoeFriday |
P205274
|
FINISHED |
| Object | junior partner |
—
|
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: junior partner | Statement: [Pep Streebek, relationshipToJoeFriday, junior partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJoeFriday Context triple: [Pep Streebek, relationshipToJoeFriday, junior partner]
-
A.
relationshipToJoeCinque
Indicates a specified type of relationship or connection that an entity has to Joe Cinque.
-
B.
relationshipToJack
Indicates the specific type of personal or social connection an entity has with Jack.
-
C.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
-
D.
relationshipToJoeGillis
Indicates the specific type of personal or social relationship that one entity has to Joe Gillis.
-
E.
relationshipToMike
Indicates the specific type of personal, social, or familial relationship that an entity has with Mike.
- 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_69f3499f8cbc81908de6ec89fa91ea8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:50 a.m.