Triple
T10974628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hero |
E259335
|
entity |
| Predicate | basedOnWorkLanguage |
P85137
|
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: [Hero, basedOnWorkLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnWorkLanguage Context triple: [Hero, basedOnWorkLanguage, English]
-
A.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
B.
languageOfUnderlyingWork
chosen
Indicates the language in which the original or underlying work (from which a derived or related work stems) is expressed.
-
C.
workTranslatedFrom
Indicates that a work is a translation derived from an original work in another language.
-
D.
hasWorkedInLanguage
Indicates that an entity has performed work or professional activities using a particular language.
-
E.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f3794c8190b1992b4695139b62 |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e8c27cc81908050590b7a04cafd |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:24 p.m.