Triple
T23169359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man in Black |
E578801
|
entity |
| Predicate | hasFullCarDesignation |
P151201
|
FINISHED |
| Object | black No. 3 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: black No. 3 car | Statement: [The Man in Black, hasFullCarDesignation, black No. 3 car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFullCarDesignation Context triple: [The Man in Black, hasFullCarDesignation, black No. 3 car]
-
A.
hasCarClass
Indicates that one entity is associated with, or categorized under, a particular class or type of car.
-
B.
hasChassisType
Indicates that an entity is associated with or equipped with a specific type of chassis.
-
C.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
D.
hasHatchback
Indicates that one entity possesses or is characterized by having a hatchback-style vehicle or body type.
-
E.
hasCarConstructor
Indicates that an entity is associated with a specific car constructor (manufacturer or builder) responsible for producing its car.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f2e5e208190839ec37de4b974af |
completed | April 29, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b75e2708190ba48875e36f983bc |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4:03 p.m.