Triple
T5693223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Master of Disguise |
E125474
|
entity |
| Predicate | hasOccupationOfProtagonist |
P21567
|
FINISHED |
| Object | CIA officer |
—
|
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: CIA officer | Statement: [The Master of Disguise, hasOccupationOfProtagonist, CIA officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOccupationOfProtagonist Context triple: [The Master of Disguise, hasOccupationOfProtagonist, CIA officer]
-
A.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
B.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
C.
requiredOccupationOf
Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
-
D.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c0e0408190ab6c3cd3f907e80f |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:44 p.m.