Triple
T21389541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lacey Farrell |
E527603
|
entity |
| Predicate | plotCatalyst |
P2762
|
FINISHED |
| Object | witnessing a client’s murder |
—
|
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: witnessing a client’s murder | Statement: [Lacey Farrell, plotCatalyst, witnessing a client’s murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plotCatalyst Context triple: [Lacey Farrell, plotCatalyst, witnessing a client’s murder]
-
A.
plotElement
chosen
Indicates that one entity functions as a narrative component or structural element within the storyline of another entity (such as a work of fiction or media).
-
B.
plotter
Indicates that one entity is a device or tool used by another entity to produce precise graphical or plotted output.
-
C.
chartDepiction
Indicates that one entity is a chart that visually represents or depicts information about another entity.
-
D.
visualizationLibrary
Indicates that an entity uses, depends on, or is implemented with a particular visualization library for rendering or displaying visual data.
-
E.
hasPlot
Indicates that an entity (such as a narrative work) possesses or is associated with a specific storyline or sequence of events.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0f8ae288190b43df9fe2841a822 |
completed | April 22, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:13 p.m.