Triple
T35482562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fingers |
E1025504
|
entity |
| Predicate | inWorldLanguage |
P12203
|
FINISHED |
| Object | Common Tongue |
—
|
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: Common Tongue | Statement: [The Fingers, inWorldLanguage, Common Tongue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inWorldLanguage Context triple: [The Fingers, inWorldLanguage, Common Tongue]
-
A.
isWorldLanguage
Indicates that a language is widely used across multiple countries or regions and serves as a common means of communication beyond its original native community.
-
B.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
C.
otherLanguage
chosen
Indicates that an entity has or uses an additional language distinct from its primary or main language.
-
D.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
-
E.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
- 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_69f76dfbcdd881908c7b0b6bc502252b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.