Triple
T30721620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations Whitaker Report |
E782168
|
entity |
| Predicate | typeOfStudy |
P98383
|
FINISHED |
| Object | special rapporteur report |
—
|
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: special rapporteur report | Statement: [United Nations Whitaker Report, typeOfStudy, special rapporteur report]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfStudy Context triple: [United Nations Whitaker Report, typeOfStudy, special rapporteur report]
-
A.
studType
Indicates a relationship where an entity is classified as a particular type or category of stud (e.g., a specific kind of fastener or structural element).
-
B.
partOfStudy
Indicates that something is a component, segment, or subset within a larger study or research project.
-
C.
studyType
chosen
Indicates the kind or category of study or research methodology associated with an entity or activity.
-
D.
dimensionOfStudy
Indicates the specific field, aspect, or perspective that characterizes or structures a particular study or research activity.
-
E.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
- 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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff7ae5d088819089aa3b6360b6b749 |
completed | May 9, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69ff7a4df6488190bf60d675b36b1d6d |
completed | May 9, 2026, 6:17 p.m. |
Created at: April 29, 2026, 8:36 p.m.