Triple
T25199538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Policenauts |
E631087
|
entity |
| Predicate | hasFanTranslation |
P2303
|
FINISHED |
| Object | English fan translation patch |
—
|
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 fan translation patch | Statement: [Policenauts, hasFanTranslation, English fan translation patch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFanTranslation Context triple: [Policenauts, hasFanTranslation, English fan translation patch]
-
A.
hasFanInterpretation
Indicates that there exists a fan-created interpretation, theory, or reading associated with the given entity or work.
-
B.
hasFan
Indicates that an entity is the admirer, supporter, or enthusiast of another entity.
-
C.
hasTranslation
chosen
Indicates that one entity is a translation or translated version of another entity in a different language.
-
D.
hasWorkTranslatedInto
Indicates that a work has been translated into a specified language or target work.
-
E.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
- 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_69e75a8b86c4819089eda22c843b739f |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 21, 2026, 12:51 p.m.