Triple
T4212893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mothra |
E93945
|
entity |
| Predicate | languageMediators |
P5475
|
FINISHED |
| Object | twin fairies |
—
|
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: twin fairies | Statement: [Mothra, languageMediators, twin fairies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageMediators Context triple: [Mothra, languageMediators, twin fairies]
-
A.
translator
chosen
Indicates that one entity serves to convert or render content from one language or form into another for a second entity.
-
B.
languageAgency
Indicates that an entity (such as a person or organization) has the capacity or authority to use, manage, or act through a particular language in performing actions or making decisions.
-
C.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
E.
languagePair
Indicates a relationship that associates two specific languages as a paired combination, typically for translation, comparison, or mapping between them.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.