Triple
T9134869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skechers |
E219174
|
entity |
| Predicate | hasKeyPerson |
P256
|
FINISHED |
| Object | Robert Greenberg |
E780576
|
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: Robert Greenberg | Statement: [Skechers, hasKeyPerson, Robert Greenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Greenberg Context triple: [Skechers, hasKeyPerson, Robert Greenberg]
-
A.
Robert Greenberg
chosen
Robert Greenberg is an American entrepreneur best known as the founder and longtime CEO of Skechers, a major global footwear company.
-
B.
Steve Greenberg
Steve Greenberg is an American sports media executive and entrepreneur best known for founding the Classic Sports Network, which later became ESPN Classic.
-
C.
Roger Greenberg
Roger Greenberg is the neurotic, self-absorbed protagonist of the 2010 Noah Baumbach film "Greenberg," portrayed by Ben Stiller.
-
D.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
-
E.
Michael Fishman
Michael Fishman is an American actor best known for playing D.J. Conner on the long-running sitcom "Roseanne" and its revival.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8de0dec8190978c80b9ec8bf25c |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05452acb481909fcf5f826caa6ae6 |
completed | April 3, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:18 p.m.