Triple
T3295009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Piven |
E69193
|
entity |
| Predicate | numberOfPrimetimeEmmyAwardsForEntourage |
P47810
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Jeremy Piven, numberOfPrimetimeEmmyAwardsForEntourage, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrimetimeEmmyAwardsForEntourage Context triple: [Jeremy Piven, numberOfPrimetimeEmmyAwardsForEntourage, 3]
-
A.
numberOfPrimetimeEmmysForTheSopranos
Indicates the count of Primetime Emmy Awards that the TV series "The Sopranos" has received.
-
B.
emmyAwardFor
Indicates that an entity has received or is associated with a specific Emmy Award for a particular work or achievement.
-
C.
numberOfTonyAwards
Indicates the total count of Tony Awards that an entity has received.
-
D.
hasWonEGOT
Indicates that an individual has won all four major entertainment awards: an Emmy, a Grammy, an Oscar, and a Tony.
-
E.
tonyNominations
Indicates that an entity has received one or more nominations for a Tony Award.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb07661748190bf57469e101c5283 |
completed | March 8, 2026, 5:23 p.m. |
| PD | Predicate disambiguation | batch_69ada42407dc81909f60d7a14e1b7934 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada526764881908e4bd52938d5374d |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:10 p.m.