Triple
T4236742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MAHLI |
E94711
|
entity |
| Predicate | canAutofocus |
P30852
|
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: [MAHLI, canAutofocus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canAutofocus Context triple: [MAHLI, canAutofocus, true]
-
A.
mayProvideFocus
Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
-
B.
canAutomate
chosen
Indicates that one entity has the capability to perform, control, or execute another entity’s process or task automatically without continuous human intervention.
-
C.
canControl
Indicates that one entity has the ability or authority to direct, manage, or influence the behavior or state of another entity.
-
D.
hasNoConventionalFocalPoint
Indicates that something lacks a single, traditional center of attention or primary point that visually or conceptually draws focus.
-
E.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e7422a88190955f5f4347fa80d2 |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f3bd188190b0cd613e8a5c1683 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:05 p.m.