Triple
T9134870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skechers |
E219174
|
entity |
| Predicate | roleOfRobertGreenberg |
P87314
|
FINISHED |
| Object | chief executive officer |
—
|
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: chief executive officer | Statement: [Skechers, roleOfRobertGreenberg, chief executive officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfRobertGreenberg Context triple: [Skechers, roleOfRobertGreenberg, chief executive officer]
-
A.
roleOfPeter Seligmann
Indicates that the specified role or position is held by Peter Seligmann.
-
B.
roleOfTedLeonsis
Indicates that the subject holds or is associated with a specific role, position, or capacity in relation to Ted Leonsis.
-
C.
roleOfHowardLutnick
Indicates that the specified role or position is held by Howard Lutnick.
-
D.
roleOfGregNorton
Indicates that Greg Norton holds or performs a particular role or function in relation to another entity.
-
E.
roleOfLeonard S. Schleifer
Indicates that the specified entity holds or has held a particular professional or organizational role associated with Leonard S. Schleifer.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8de0dec8190978c80b9ec8bf25c |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc6601d77881908299d58db6e64937 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:18 p.m.