Triple
T31352089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Who Dat Ninja |
E799622
|
entity |
| Predicate | hasFictionalLeadCharacter |
P197057
|
FINISHED |
| Object | a ninja played by Tracy Jordan |
—
|
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: a ninja played by Tracy Jordan | Statement: [Who Dat Ninja, hasFictionalLeadCharacter, a ninja played by Tracy Jordan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalLeadCharacter Context triple: [Who Dat Ninja, hasFictionalLeadCharacter, a ninja played by Tracy Jordan]
-
A.
hasFictionalLeader
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
-
B.
isFictionalCharacter
Indicates that the subject is a character that exists only in fiction rather than in real life.
-
C.
hasFictionalSpokesperson
Indicates that an entity is represented or promoted by a spokesperson who is a fictional or imaginary character.
-
D.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
E.
isFictionalPersonFrom
Indicates that a fictional person originates from or is associated with a particular place or source.
- 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_69f224e5e9bc8190a16339328897c4f8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69fe7663b5bc81909524c40d3a172512 |
completed | May 8, 2026, 11:48 p.m. |
Created at: April 29, 2026, 9:17 p.m.