Triple
T95868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norsk Data NORD-10 |
E1928
|
entity |
| Predicate | wordLength |
P4117
|
FINISHED |
| Object | 16-bit |
—
|
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: 16-bit | Statement: [Norsk Data NORD-10, wordLength, 16-bit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wordLength Context triple: [Norsk Data NORD-10, wordLength, 16-bit]
-
A.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
B.
width
Indicates the measurement of how wide an entity is, typically the extent of its horizontal dimension from side to side.
-
C.
hasStandardLetterCount
Indicates that an entity’s associated text or label contains a number of letters that matches a predefined standard or expected count.
-
D.
numberOfSpans
Indicates the total count of distinct spans or segments associated with an entity or within a specified context.
-
E.
dayLengthCharacteristic
Indicates a relationship where an entity is characterized or defined by the length or duration of its day.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a250ca7eec8190b31f7e61f5e3ee1f |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.