Triple
T11306237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FICON |
E267719
|
entity |
| Predicate | dataRateType |
P1376
|
FINISHED |
| Object | multi-gigabit per second |
—
|
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: multi-gigabit per second | Statement: [FICON, dataRateType, multi-gigabit per second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataRateType Context triple: [FICON, dataRateType, multi-gigabit per second]
-
A.
dataRate
chosen
Indicates the rate at which data is transmitted, processed, or transferred between entities over a given time interval.
-
B.
dataRateGeneration
Indicates the rate at which data is produced or generated over time in a given context.
-
C.
hasRateType
Indicates the specific category or scheme under which a rate (such as a price, fee, or interest) is defined or applied.
-
D.
rechargeRate
Indicates the rate or speed at which something restores or replenishes its capacity, energy, or resources over time.
-
E.
spreadingRateType
Indicates the manner or category of how quickly or in what way something spreads or propagates.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a7255c81909675fe9ad6d71934 |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.