Triple
T1531903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Database System Concepts |
E32460
|
entity |
| Predicate | isWidelyUsed |
P29905
|
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: [Database System Concepts, isWidelyUsed, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWidelyUsed Context triple: [Database System Concepts, isWidelyUsed, true]
-
A.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
B.
mostWidelyUsedImplementationOf
Indicates that one implementation of something is the most commonly or widely used version among all its implementations.
-
C.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
D.
isUsedUnder
Indicates that one entity is utilized or applied within the context, conditions, or framework defined by another entity.
-
E.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a933ddc5a881909cdf503f2bc29bd4 |
completed | March 5, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69a907ae8f688190ad9000ea1e018585 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a933dce3488190b20f0e3d37d16371 |
completed | March 5, 2026, 7:42 a.m. |
Created at: March 4, 2026, 7:26 p.m.