Triple
T31352071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Who Dat Ninja |
E799622
|
entity |
| Predicate | hasFictionalActor |
P114999
|
FINISHED |
| Object | Tracy Jordan |
—
|
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: Tracy Jordan | Statement: [Who Dat Ninja, hasFictionalActor, Tracy Jordan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalActor Context triple: [Who Dat Ninja, hasFictionalActor, Tracy Jordan]
-
A.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
B.
hasFictionalPerformer
Indicates that an entity is associated with a performer who is a fictional or imaginary character rather than a real person.
-
C.
hasFictionalCoStar
chosen
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
D.
isFictionalPersonFrom
Indicates that a fictional person originates from or is associated with a particular place or source.
-
E.
hasFictionalSpeaker
Indicates that a work, text, or expression is presented as being spoken by an invented or non-real speaker rather than an actual person.
- 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_69f224e5e9bc8190a16339328897c4f8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe744faca881908e11e90e0a35653f |
completed | May 8, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69fe734cbf7081909a552c5cf3b5ea59 |
completed | May 8, 2026, 11:35 p.m. |
Created at: April 29, 2026, 9:17 p.m.