Triple
T6167975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Case of the Curious Bride |
E137617
|
entity |
| Predicate | featuresProfessionOfProtagonist |
P21567
|
FINISHED |
| Object | lawyer |
—
|
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: lawyer | Statement: [The Case of the Curious Bride, featuresProfessionOfProtagonist, lawyer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresProfessionOfProtagonist Context triple: [The Case of the Curious Bride, featuresProfessionOfProtagonist, lawyer]
-
A.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
B.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
C.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
D.
protagonistField
Indicates that the subject is the main or central character (protagonist) within the specified narrative or context.
-
E.
creativeRole
Indicates that an entity holds a specific creative function or responsibility in relation to another entity, such as a work or project.
- 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_69c008a68c508190a8d78245c865960e |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d647ae48190a1db07b4f4a06e67 |
completed | March 22, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69c055f5b81481908819515cdc334ae6 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:18 p.m.