Triple
T7304468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zilog Z80 |
E167939
|
entity |
| Predicate | hasAlternateRegisterSet |
P76104
|
FINISHED |
| Object | AF′ |
—
|
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: AF′ | Statement: [Zilog Z80, hasAlternateRegisterSet, AF′]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateRegisterSet Context triple: [Zilog Z80, hasAlternateRegisterSet, AF′]
-
A.
hasAlternateCut
Indicates that an entity has an alternative edited version or cut, distinct from its primary or original form.
-
B.
hasAlternateMemberType
Indicates that an entity is associated with a different or substitute type of member than its primary or standard member type.
-
C.
hasStandardRegister
Indicates that something is expressed or occurs in a standard, neutral, or non-marked linguistic register.
-
D.
hasAlternativeMIC
Indicates that an entity is associated with an alternative minimum inhibitory concentration (MIC) value, representing a different measured or applicable MIC than the primary one.
-
E.
hasAlternativeContext
Indicates that something is associated with an additional or different contextual setting or interpretation beyond its primary one.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebb352ec8190846eff044e08805e |
completed | March 27, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69c6e76e67d88190bd3ca6864f45845a |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6eb2d4c0c8190b4cc6fdfdb7f4827 |
completed | March 27, 2026, 8:40 p.m. |
Created at: March 27, 2026, 3:01 p.m.