Triple
T3224438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophie Sheridan |
E67589
|
entity |
| Predicate | setsInMotion |
P46318
|
FINISHED |
| Object | plot of Mamma Mia! |
—
|
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: plot of Mamma Mia! | Statement: [Sophie Sheridan, setsInMotion, plot of Mamma Mia!]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setsInMotion Context triple: [Sophie Sheridan, setsInMotion, plot of Mamma Mia!]
-
A.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
B.
setsForth
Indicates that an entity formally presents, explains, or lays out something such as a plan, argument, rule, or proposal.
-
C.
sets
Indicates that an entity places, positions, or puts another entity into a particular state, location, or configuration.
-
D.
set
Indicates that an entity places, positions, or establishes another entity into a particular state, configuration, or location.
-
E.
modelsMotionOf
Indicates that one entity provides a representation or simulation of the motion or movement behavior of 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adae1ae8f08190880d0f0e8539cdbc |
completed | March 8, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0bb6c48190a0659c67d40ee37c |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada149df58819091173b14b49582b1 |
completed | March 8, 2026, 4:18 p.m. |
Created at: March 8, 2026, 3:08 p.m.