Triple
T8433572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drax the Destroyer |
E199171
|
entity |
| Predicate | languageTrait |
P83334
|
FINISHED |
| Object | takes everything literally |
—
|
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: takes everything literally | Statement: [Drax the Destroyer, languageTrait, takes everything literally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageTrait Context triple: [Drax the Destroyer, languageTrait, takes everything literally]
-
A.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
B.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
-
C.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
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.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
- F. None of above. chosen
Provenance (4 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0ec200c8190b0299e2b0b4bdcc2 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe30c2d088190b4cb89adb4e88273 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:07 p.m.