Triple
T1924226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Naked Sun |
E40191
|
entity |
| Predicate | featuresRobots |
P6774
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Naked Sun, featuresRobots, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresRobots Context triple: [The Naked Sun, featuresRobots, yes]
-
A.
equipmentCharacteristic
Indicates that a specific characteristic, property, or attribute is associated with a piece of equipment.
-
B.
technologicalFeature
chosen
Indicates that one entity possesses, exhibits, or is characterized by a specific technological capability, component, or functionality in relation to another entity.
-
C.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
D.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
-
E.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2359ca0819082b514a34c469b21 |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafeec6f881909d47acb966683279 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.