Triple
T28941943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank the Thunderbird |
E730473
|
entity |
| Predicate | languageUniverse |
P164802
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Frank the Thunderbird, languageUniverse, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUniverse Context triple: [Frank the Thunderbird, languageUniverse, English]
-
A.
languageOfFictionalUniverse
Indicates the language used or spoken within a fictional universe or setting.
-
B.
fictionalUniverseLanguage
chosen
Indicates that a language is used or exists within a particular fictional universe.
-
C.
hasLanguageInUniverse
Indicates that a particular language exists or is used within a specified fictional or conceptual universe.
-
D.
otherLanguage
Indicates that an entity has or uses an additional language distinct from its primary or main language.
-
E.
languageDiversity
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
- 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_69f043ea0aa88190a25acbf46157995a |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
Created at: April 28, 2026, 8:37 a.m.