Triple
T9532549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VT100 |
E229930
|
entity |
| Predicate | supportsCursorAddressing |
P88580
|
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: [VT100, supportsCursorAddressing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCursorAddressing Context triple: [VT100, supportsCursorAddressing, true]
-
A.
supportsByteAddressing
Indicates that one entity provides the capability for direct access to individual bytes within its addressable memory or data space for another entity.
-
B.
supportsAddressTypes
Indicates that an entity is capable of handling or working with one or more specified types of addresses.
-
C.
supportsAt
Indicates that one entity provides assistance, endorsement, or backing to another entity in a specific context, location, or point in time.
-
D.
supportsKeyboardAndMouse
Indicates that the subject provides compatibility with and can be operated using both a keyboard and a mouse.
-
E.
addressingMechanism
Indicates the method or system used to identify, locate, or reference a target within a larger space, network, or structure.
- 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_69ca8479934c81908006d0e6e970ae05 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98b5651881908241b040f123c6a8 |
completed | April 1, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69cca56c44f88190a54a5d2a133bb07e |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca89f1d748190bf3636bea28d8a37 |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 8 p.m.