Triple
T10259077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Two Gentlemen of Verona |
E240546
|
entity |
| Predicate | featuresPlotDevice |
P80690
|
FINISHED |
| Object | love triangle |
—
|
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: love triangle | Statement: [The Two Gentlemen of Verona, featuresPlotDevice, love triangle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresPlotDevice Context triple: [The Two Gentlemen of Verona, featuresPlotDevice, love triangle]
-
A.
featuresDevice
Indicates that one entity includes, incorporates, or provides the other entity as a device within it or as part of its functionality.
-
B.
featuresIn
chosen
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
equipmentCharacteristic
Indicates that a specific characteristic, property, or attribute is associated with a piece of equipment.
-
D.
featuresFictionalTechnology
Indicates that an entity includes, depicts, or makes use of imagined or speculative technology that does not exist in reality.
-
E.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69d4d1edae6881909a65201b8e51ea0a |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:31 a.m.