Triple
T5741833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway magazine |
E126631
|
entity |
| Predicate | languageInUniverse |
P43064
|
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: [Runway magazine, languageInUniverse, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageInUniverse Context triple: [Runway magazine, languageInUniverse, English]
-
A.
languageOfFictionalUniverse
chosen
Indicates the language used or spoken within a fictional universe or setting.
-
B.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
C.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
D.
hasFictionalUniverseGenre
Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
-
E.
languageOfVisionaries
Indicates a relationship where a particular language is associated with, used by, or characteristic of visionary individuals or thinkers.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b52663c8190ab44258468d4296d |
completed | March 22, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c021ca61688190875bd6107161c284 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.