Triple
T2752474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ACM Transactions on Architecture and Code Optimization |
E61019
|
entity |
| Predicate | scholarly |
P28837
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [ACM Transactions on Architecture and Code Optimization, scholarly, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scholarly Context triple: [ACM Transactions on Architecture and Code Optimization, scholarly, true]
-
A.
scholarlyUse
Indicates that something is used for academic, educational, or research-related purposes.
-
B.
scholarlyView
Indicates that one entity holds an academic or research-based interpretation, opinion, or theoretical stance about another entity.
-
C.
isScholarly
chosen
Indicates that an entity exhibits characteristics of academic rigor, research-based inquiry, and adherence to scholarly standards or conventions.
-
D.
academicApproach
Indicates an entity’s characteristic method, strategy, or style used in academic work, study, or instruction.
-
E.
hasNotableScholar
Indicates that an entity is associated with a scholar who is recognized as particularly distinguished or influential in relation to that entity.
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb6d08088190b489de15a120ba3f |
completed | March 7, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69abd82d005c81908a1ac7a1313c6d88 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.