Triple
T35365409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thanksgiving (2023 film) |
E1021614
|
entity |
| Predicate | hasFauxTrailerOrigin |
P195836
|
FINISHED |
| Object | Thanksgiving (fake trailer in Grindhouse) |
—
|
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: Thanksgiving (fake trailer in Grindhouse) | Statement: [Thanksgiving (2023 film), hasFauxTrailerOrigin, Thanksgiving (fake trailer in Grindhouse)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFauxTrailerOrigin Context triple: [Thanksgiving (2023 film), hasFauxTrailerOrigin, Thanksgiving (fake trailer in Grindhouse)]
-
A.
hasTrailOrigin
Indicates that a trail begins or originates from a specified location or entity.
-
B.
hasTrailerCar
Indicates that one vehicle is connected to and pulling another vehicle configured as a trailer car.
-
C.
hasTrailFeature
Indicates that a trail possesses or is characterized by a specific feature or attribute.
-
D.
hasFakeIDName
Indicates that an entity possesses or uses a name associated with a fake or fraudulent identification document.
-
E.
hasSeparateTrailingTruck
Indicates that an entity is accompanied by a distinct, independently attached trailing truck or carriage rather than having it integrated into its main structure.
- 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
| PDg | Predicate description generation | batch_69fde9fb68388190ada4a7018e2a2f76 |
completed | May 8, 2026, 1:49 p.m. |
Created at: May 3, 2026, 4:03 p.m.