Triple
T2374683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbia Human Rights Law Review |
E46168
|
entity |
| Predicate | hasEditorType |
P38783
|
FINISHED |
| Object | law students |
—
|
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: law students | Statement: [Columbia Human Rights Law Review, hasEditorType, law students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEditorType Context triple: [Columbia Human Rights Law Review, hasEditorType, law students]
-
A.
hasEditorScripting
Indicates that an entity provides or supports scripting capabilities specifically for editing or editor-related functionality.
-
B.
hasEditionType
Indicates that one entity is a specific edition type or format classification of another entity (such as a work, publication, or product).
-
C.
hasEditingModel
Indicates that one entity is associated with another entity that serves as its editing or modification model.
-
D.
hasDefaultTextEditor
Indicates that one entity is designated as the standard or primary text editor used by another entity.
-
E.
hasEditorialContent
Indicates that an entity includes or is associated with editorially created or curated content, such as articles, commentary, or opinion pieces.
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abca4d89248190be7d712d5fa8382b |
completed | March 7, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69abc59d82f08190b7c36982d1ae783d |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abca4c937c8190b4dfca716b868d4f |
completed | March 7, 2026, 6:48 a.m. |
Created at: March 4, 2026, 7:56 p.m.