Triple
T8507758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DRAM |
E201374
|
entity |
| Predicate | timingParameter |
P82883
|
FINISHED |
| Object | CAS latency |
—
|
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: CAS latency | Statement: [DRAM, timingParameter, CAS latency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timingParameter Context triple: [DRAM, timingParameter, CAS latency]
-
A.
timingMethod
Indicates the method or technique used to measure or record the timing of an event or process.
-
B.
timingStandard
Indicates that one entity specifies or conforms to the timing rules, constraints, or reference schedule defined by another entity.
-
C.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
D.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
-
E.
timingOfRace
Indicates the temporal details or schedule associated with a race, such as its start time, duration, or overall timing.
- 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_69ca8320e5748190ac2c585a0bba8193 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5de18448190a695eec609b34e1a |
completed | March 31, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:14 p.m.