Triple
T1156949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honeywell 316 |
E24403
|
entity |
| Predicate | mainMemoryTechnology |
P9901
|
FINISHED |
| Object | magnetic core memory |
—
|
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: magnetic core memory | Statement: [Honeywell 316, mainMemoryTechnology, magnetic core memory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainMemoryTechnology Context triple: [Honeywell 316, mainMemoryTechnology, magnetic core memory]
-
A.
primaryMemoryType
chosen
Indicates the main or dominant type of memory associated with or used by an entity in a given context.
-
B.
memoryType
Indicates the specific category or kind of memory associated with an entity or process.
-
C.
hasRAM
Indicates that an entity possesses or is equipped with a specified amount or type of random-access memory (RAM).
-
D.
memoryModel
Indicates a relationship where an entity serves as or uses a specific model or framework for representing, organizing, or managing memory.
-
E.
memoryBandwidth
Indicates the rate at which data can be transferred to or from a memory system over a given period of time.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc92ae008190a587c12ecc9a502a |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb50d19c81908a98dbbb04a8906f |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.