Triple
T27165571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viscos |
E682772
|
entity |
| Predicate | languageOfInhabitantsInFiction |
P70771
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Viscos, languageOfInhabitantsInFiction, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfInhabitantsInFiction Context triple: [Viscos, languageOfInhabitantsInFiction, French]
-
A.
languageOfFictionalUniverse
Indicates the language used or spoken within a fictional universe or setting.
-
B.
fictionalUniverseLanguage
Indicates that a language is used or exists within a particular fictional universe.
-
C.
fictionalLanguage
Indicates a relationship where an entity uses, is expressed in, or is associated with a language that is invented or does not exist in reality.
-
D.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
E.
hasLanguageInUniverse
chosen
Indicates that a particular language exists or is used within a specified fictional or conceptual universe.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
Created at: April 27, 2026, 9:21 a.m.