Triple
T1499613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intel 4004 |
E29765
|
entity |
| Predicate | canAddress |
P28526
|
FINISHED |
| Object | up to 16 registers |
—
|
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: up to 16 registers | Statement: [Intel 4004, canAddress, up to 16 registers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canAddress Context triple: [Intel 4004, canAddress, up to 16 registers]
-
A.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
B.
supportsAddressTypes
Indicates that an entity is capable of handling or working with one or more specified types of addresses.
-
C.
hasAddressState
Indicates that an entity’s address is located within a particular state or state-level administrative region.
-
D.
canElect
Indicates that one entity has the authority or ability to choose another entity for a position, role, or office through an election process.
-
E.
usesAddressingSystem
Indicates that one entity employs or applies a particular addressing system associated with another entity.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6f0ce988190aafab4a6e0dfd710 |
completed | March 1, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69a4c48a8cf48190a6ebf8d44a608a06 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c4feea448190b2b5071b28a5b608 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8:12 p.m.