Triple
T15329982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Partners (2014 TV series) |
E366506
|
entity |
| Predicate | plotOutline |
P24126
|
FINISHED |
| Object | Two very different lawyers become partners in a Chicago 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: Two very different lawyers become partners in a Chicago law firm. | Statement: [Partners (2014 TV series), plotOutline, Two very different lawyers become partners in a Chicago law firm.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plotOutline Context triple: [Partners (2014 TV series), plotOutline, Two very different lawyers become partners in a Chicago law firm.]
-
A.
storyline
chosen
Indicates that one entity serves as the narrative plot or sequence of events associated with another entity.
-
B.
partOfPlot
Indicates that one event, action, or element is a constituent component within the overall plot of a narrative.
-
C.
plotDetail
Indicates that one entity provides specific information or events that elaborate on the storyline of another entity.
-
D.
plotInvolvement
Indicates that an entity participates in, contributes to, or is affected by the events or storyline of a narrative work.
-
E.
taskInPlot
Indicates that a specific task occurs within, is associated with, or is part of a particular plot or storyline.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0161ac8190aa1d52c063c02ad0 |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:17 a.m.