Triple
T29050814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earth (Marvel Cinematic Universe) |
E735256
|
entity |
| Predicate | hasOtherLanguages |
P35567
|
FINISHED |
| Object | multiple human languages |
—
|
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: multiple human languages | Statement: [Earth (Marvel Cinematic Universe), hasOtherLanguages, multiple human languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOtherLanguages Context triple: [Earth (Marvel Cinematic Universe), hasOtherLanguages, multiple human languages]
-
A.
hasLanguages
chosen
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
B.
hasSecondaryLanguage
Indicates that an entity possesses or uses a secondary language in addition to its primary language.
-
C.
hasRelatedLanguage
Indicates that one language is related to another through shared linguistic origins, features, or classification.
-
D.
hasNeighboringLanguages
Indicates that two languages are geographically or regionally adjacent to each other in their areas of use.
-
E.
wroteInMultipleLanguages
Indicates that an entity authored written works using more than one 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_69f077e64b88819094d37bdbca8191b3 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f66065c17081908a0bb6b8a7f16558 |
completed | May 2, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 10:08 a.m.