Triple
T3445977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara Bain |
E72678
|
entity |
| Predicate | notableCharacterTraitOfRoleCinnamonCarter |
P37384
|
FINISHED |
| Object | disguise expert |
—
|
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: disguise expert | Statement: [Barbara Bain, notableCharacterTraitOfRoleCinnamonCarter, disguise expert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCharacterTraitOfRoleCinnamonCarter Context triple: [Barbara Bain, notableCharacterTraitOfRoleCinnamonCarter, disguise expert]
-
A.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
B.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
-
C.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or story associated with another entity.
-
D.
hasSupportingCharacterTrait
Indicates that a supporting character possesses a particular trait, quality, or characteristic.
-
E.
hasEnigmaticCharacter
Indicates that something possesses a mysterious, puzzling, or difficult-to-interpret quality or nature.
- 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba2cc3048190ab1385699387df8d |
completed | March 8, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69adae0255b48190a9069f7871c7a012 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:16 p.m.