Triple
T17023074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Williams tube |
E412992
|
entity |
| Predicate | storesBitsAs |
P48585
|
FINISHED |
| Object | charged and uncharged spots |
—
|
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: charged and uncharged spots | Statement: [Williams tube, storesBitsAs, charged and uncharged spots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storesBitsAs Context triple: [Williams tube, storesBitsAs, charged and uncharged spots]
-
A.
bitRepresentation
chosen
Indicates that one entity is the binary (bit-level) representation or encoding of another entity.
-
B.
storesObjectsAs
Indicates that one entity keeps or maintains other entities within it as stored items or contents.
-
C.
bitWidth
Indicates the number of bits used to represent or encode a given value, type, or data element.
-
D.
bitOrder
Indicates the ordering or sequence of bits within a binary representation, such as which bit positions are considered first or most significant.
-
E.
bitSlice
Indicates taking a contiguous subset of bits from a larger bit sequence, defined by specified start and end positions.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d2abbc81908943becf5f539fc6 |
completed | April 18, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.