Triple
T1931554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac OS 9 |
E40955
|
entity |
| Predicate | supportsMemoryProtection |
P33566
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Mac OS 9, supportsMemoryProtection, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMemoryProtection Context triple: [Mac OS 9, supportsMemoryProtection, no]
-
A.
hasRAM
Indicates that an entity possesses or is equipped with a specified amount or type of random-access memory (RAM).
-
B.
protectsFeature
Indicates that one entity safeguards, preserves, or defends a particular feature or characteristic of another entity.
-
C.
providesProtectionAgainst
Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
-
D.
isStrongerProtectionThan
Indicates that one form of protection provides a higher level of security, defense, or safeguarding compared to another.
-
E.
protectionType
Indicates the kind or method of protection that is applied to or associated with an entity.
- 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_69a8864711648190b07bed24ed76258e |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb297ec2c819092ad62d72005223d |
completed | March 7, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69abafeec6f881909d47acb966683279 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb20c4970819086e66a5435744297 |
completed | March 7, 2026, 5:05 a.m. |
Created at: March 4, 2026, 7:35 p.m.