Triple
T36691067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toshiba P300 |
E905956
|
entity |
| Predicate | dataConnector |
P37199
|
FINISHED |
| Object | SATA data connector |
—
|
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: SATA data connector | Statement: [Toshiba P300, dataConnector, SATA data connector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataConnector Context triple: [Toshiba P300, dataConnector, SATA data connector]
-
A.
dataIntegration
Indicates that data from multiple sources is combined, transformed, and unified into a single, coherent dataset or system.
-
B.
notableConnector
Indicates that one entity serves as a significant link, bridge, or intermediary that meaningfully connects or relates two other entities.
-
C.
dataAcquisition
Indicates the process by which one entity obtains, collects, or retrieves data from another source or system.
-
D.
dataContext
Indicates the situational or environmental conditions under which data is produced, interpreted, or used, such as source, scope, assumptions, and relevant constraints.
-
E.
dataInterface
chosen
Indicates that one entity serves as a data interface through which another entity can access, exchange, or manipulate data.
- 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_69f76e70d2448190bdd3ce781ba971c5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c7c767cc81909fbed9de6af09e55 |
completed | May 3, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.