Triple
T32591395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura Dern as Lula Pace Fortune |
E833074
|
entity |
| Predicate | belongsToFranchiseOrCycle |
P187796
|
FINISHED |
| Object | David Lynch films |
—
|
NE NERFINISHED |
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: David Lynch films | Statement: [Laura Dern as Lula Pace Fortune, belongsToFranchiseOrCycle, David Lynch films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToFranchiseOrCycle Context triple: [Laura Dern as Lula Pace Fortune, belongsToFranchiseOrCycle, David Lynch films]
-
A.
sitsWithinFranchise
chosen
Indicates that one entity is part of, or belongs to, a larger franchise or franchise system.
-
B.
hasFranchiseRelation
Indicates a relationship where one entity holds franchise rights or operates under the brand, business model, or authorization of another entity.
-
C.
hasFranchiseRole
Indicates that an entity holds a specific role or position within a franchise relationship.
-
D.
belongsToCycle
Indicates that an entity is part of, or contained within, a specific cycle or cyclic structure.
-
E.
hasFranchiseConnection
Indicates a relationship where two entities are linked through a franchise arrangement, such as licensing, branding, or operational affiliation within the same franchise system.
- 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_69f34929ff648190aded9424aa7564ae |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
Created at: May 1, 2026, 1:05 a.m.