Triple
T8708178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evidence |
E206703
|
entity |
| Predicate | recurringCharacterRole |
P23263
|
FINISHED |
| Object | robopsychologist |
—
|
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: robopsychologist | Statement: [Evidence, recurringCharacterRole, robopsychologist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringCharacterRole Context triple: [Evidence, recurringCharacterRole, robopsychologist]
-
A.
supportingCharacter
Indicates that one entity plays a secondary or assisting role in the story or context relative to another primary entity.
-
B.
featuresCharacterRole
chosen
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
C.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or story associated with another entity.
-
D.
hasRecurringProtagonists
Indicates that the same main character or set of main characters appears repeatedly across multiple works or installments in a series.
-
E.
cultRole
Indicates that an entity holds a specific role, position, or function within a cult or cult-like group.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58ffa6a481908866b6239d1d9b92 |
completed | March 31, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.