Triple
T15909019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Shore High School (fictional) |
E385796
|
entity |
| Predicate | languageOfInstructionFictional |
P70771
|
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: [North Shore High School (fictional), languageOfInstructionFictional, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfInstructionFictional Context triple: [North Shore High School (fictional), languageOfInstructionFictional, English]
-
A.
languageOfFictionalUniverse
Indicates the language used or spoken within a fictional universe or setting.
-
B.
fictionalLanguage
Indicates a relationship where an entity uses, is expressed in, or is associated with a language that is invented or does not exist in reality.
-
C.
languageOfPrimaryNarrations
Indicates the language in which the main or primary narrations are expressed or conveyed.
-
D.
languageWithinFiction
Indicates that a language is used or exists within the context of a fictional work or fictional universe.
-
E.
hasLanguageInUniverse
chosen
Indicates that a particular language exists or is used within a specified fictional or conceptual universe.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:52 a.m.