Triple
T471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvard University |
E9
|
entity |
| Predicate | languageOfInstruction |
P56
|
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: [Harvard University, languageOfInstruction, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfInstruction Context triple: [Harvard University, languageOfInstruction, English]
-
A.
primaryLanguageOfInstruction
chosen
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
B.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
C.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
D.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
E.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
- 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_69a22735e1b081908bd0457057dcf086 |
completed | Feb. 27, 2026, 11:22 p.m. |
| NER | Named-entity recognition | batch_69a2304aaa2c8190ab7e8dd5da977c11 |
completed | Feb. 28, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69a22918087081909e717b8bee896e8f |
completed | Feb. 27, 2026, 11:30 p.m. |
Created at: Feb. 27, 2026, 11:24 p.m.