Triple
T11343971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Olson |
E268670
|
entity |
| Predicate | hasColleague |
P398
|
FINISHED |
| Object | Pete Campbell |
E268674
|
NE 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: Pete Campbell | Statement: [Peggy Olson, hasColleague, Pete Campbell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pete Campbell Context triple: [Peggy Olson, hasColleague, Pete Campbell]
-
A.
Pete Campbell
chosen
Pete Campbell is an ambitious and often morally conflicted advertising account executive in the television drama series "Mad Men."
-
B.
Pete Miller
Pete Miller is a musician best known as a member of the Celtic rock band O'Malley's March.
-
C.
Pete Miller
Pete Miller is a character from the U.S. version of "The Office," introduced in the later seasons as a new employee at Dunder Mifflin Scranton.
-
D.
Peter Warrick
Peter Warrick is a former American football wide receiver best known for his standout college career at Florida State University and his subsequent tenure in the NFL with the Cincinnati Bengals.
-
E.
Peter Spears
Peter Spears is an American film producer and actor best known for his work on acclaimed independent films such as "Nomadland" and "Call Me by Your Name."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea1f9574819089760c5b5908f09e |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e55649a9188190911608fef5894bd8 |
completed | April 19, 2026, 10:25 p.m. |
Created at: April 8, 2026, 9:33 p.m.