Triple
T7940401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DeLorean time machine |
E184373
|
entity |
| Predicate | propType |
P6678
|
FINISHED |
| Object | film prop car |
—
|
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: film prop car | Statement: [DeLorean time machine, propType, film prop car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: propType Context triple: [DeLorean time machine, propType, film prop car]
-
A.
propUsed
Indicates that a particular property or attribute is utilized or applied in a given context or situation.
-
B.
usesProp
Indicates that one entity employs, utilizes, or makes use of a particular property, resource, or object in performing an action or fulfilling a function.
-
C.
specType
Indicates the specific type or category of a specification that an entity is associated with.
-
D.
componentType
chosen
Indicates that one entity specifies or classifies the kind or category of component that another entity represents or uses.
-
E.
propagatorType
Indicates the specific method or model used to propagate or advance a state (such as position, condition, or effect) from one point in time or space to another.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b0ac8bc8190b4e4f79b15c316b3 |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae93526d081909303265bf60419fd |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:08 p.m.