Triple
T34426804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Strong as Sebastian Graves |
E883696
|
entity |
| Predicate | workBoxOfficePerformance |
P178935
|
FINISHED |
| Object | underperformedCommercially |
—
|
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: underperformedCommercially | Statement: [Mark Strong as Sebastian Graves, workBoxOfficePerformance, underperformedCommercially]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workBoxOfficePerformance Context triple: [Mark Strong as Sebastian Graves, workBoxOfficePerformance, underperformedCommercially]
-
A.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
B.
officeIs
Indicates that one entity serves as the office or official workplace location of another entity.
-
C.
officeAfter
Indicates that one office or term of office occurs chronologically after another office or term.
-
D.
officeIn
Indicates that one entity has an office located within the premises or jurisdiction of another entity.
-
E.
mentionsOffice
Indicates that one entity explicitly refers to or brings up an office (such as a workplace, office location, or office role) in relation to another entity.
- 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_69f349c3dd2c819092cc9e64809f4a42 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f719cc31ec819099bebcf833b14d76 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71824431081908d9685d2462ea242 |
completed | May 3, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69f719458378819081725f544efb1173 |
completed | May 3, 2026, 9:45 a.m. |
Created at: May 1, 2026, 2 a.m.