Triple
T13597430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CSRL |
E324857
|
entity |
| Predicate | researchesTopic |
P24329
|
FINISHED |
| Object | racial justice |
—
|
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: racial justice | Statement: [CSRL, researchesTopic, racial justice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: researchesTopic Context triple: [CSRL, researchesTopic, racial justice]
-
A.
researchTopic
chosen
Indicates that a subject conducts or focuses research on a particular topic or area of study.
-
B.
coResearcher
Indicates that two or more individuals collaborate as peers on the same research work or project.
-
C.
researchValue
Indicates that something is considered useful, important, or relevant for research or scholarly investigation.
-
D.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
E.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0590558819080ccc5874a650b1e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.