Triple
T24095039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punch Andrews |
E596892
|
entity |
| Predicate | helpedGuideCareerOf |
P90207
|
FINISHED |
| Object | Bob Seger |
—
|
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: Bob Seger | Statement: [Punch Andrews, helpedGuideCareerOf, Bob Seger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpedGuideCareerOf Context triple: [Punch Andrews, helpedGuideCareerOf, Bob Seger]
-
A.
helpsLaunchCareerOf
chosen
Indicates that one entity plays a significant role in starting, advancing, or establishing the professional career of another entity.
-
B.
careerAssists
Indicates the total number of assists a player has recorded over the entire span of their professional or competitive career.
-
C.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
-
D.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
E.
studCareerStart
Indicates the point in time when a student's professional or academic career begins.
- 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_69e288c548048190a5c1018da1166a21 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dd2332b48190a711b2a0a304f3c2 |
completed | April 29, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 10:58 p.m.