Triple
T30330141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Firm (TV series) |
E771453
|
entity |
| Predicate | setTime |
P20835
|
FINISHED |
| Object | ten years after exposing a corrupt law firm |
—
|
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: ten years after exposing a corrupt law firm | Statement: [The Firm (TV series), setTime, ten years after exposing a corrupt law firm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setTime Context triple: [The Firm (TV series), setTime, ten years after exposing a corrupt law firm]
-
A.
timeProperty
Indicates that one entity specifies, constrains, or characterizes a temporal aspect or timing-related attribute of another entity.
-
B.
timeOfSetting
chosen
Indicates the specific time at which an event, object, or phenomenon is set, scheduled, or takes place.
-
C.
setHourRecord
Indicates updating or assigning the recorded value for a specific hour within a time-related record or schedule.
-
D.
timeSettingVariant
Indicates a relationship where one time setting is an alternative or modified version of another time setting.
-
E.
timeShiftProperty
Indicates a relationship where one property value is derived from another by applying a temporal shift (e.g., offsetting it to an earlier or later point in time).
- F. None of above.
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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
Created at: April 29, 2026, 7:53 p.m.