Triple
T14767409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franky Four Fingers |
E347032
|
entity |
| Predicate | carriesObject |
P24081
|
FINISHED |
| Object | briefcase with a large diamond |
—
|
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: briefcase with a large diamond | Statement: [Franky Four Fingers, carriesObject, briefcase with a large diamond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carriesObject Context triple: [Franky Four Fingers, carriesObject, briefcase with a large diamond]
-
A.
carriedObjects
chosen
Indicates that one entity is transporting or holding another entity as a carried item.
-
B.
carriedBy
Indicates that one entity is physically supported and transported by another entity.
-
C.
depictedHolding
Indicates that one entity is shown in an image or representation as physically holding or grasping another entity.
-
D.
canBeHeldWith
Indicates that two entities are compatible or suitable to be held or used together at the same time.
-
E.
alsoCarries
Indicates that an entity, in addition to other items or responsibilities it has, carries another specified item or load as well.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec81236f081908063bb4350b7b985 |
completed | April 14, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.