Triple
T33198270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Señor Martinez |
E849826
|
entity |
| Predicate | hasAssociatedActor |
P61782
|
FINISHED |
| Object | Ken Jeong |
—
|
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: Ken Jeong | Statement: [Señor Martinez, hasAssociatedActor, Ken Jeong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedActor Context triple: [Señor Martinez, hasAssociatedActor, Ken Jeong]
-
A.
hasAssociatedActress
Indicates that an entity is linked to an actress who is associated with it in a relevant context (e.g., participation, representation, or involvement).
-
B.
subjectHasActor
chosen
Indicates that a subject is associated with or possesses a particular actor involved in an action or process.
-
C.
hasCompanionActor
Indicates that one actor is accompanied or associated by another actor as a companion in a given context or activity.
-
D.
associatedWithActorImage
Indicates a relationship where something (such as data, content, or a record) is linked or connected to an actor’s image.
-
E.
hasAssociatedAuthority
Indicates that an entity is linked to a specific authority that holds responsibility, control, or oversight related to it.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 1, 2026, 1:29 a.m.