Triple
T300480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TRST |
E6185
|
entity |
| Predicate | scopeOfReset |
P11251
|
FINISHED |
| Object | TAP state machine |
—
|
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: TAP state machine | Statement: [TRST, scopeOfReset, TAP state machine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scopeOfReset Context triple: [TRST, scopeOfReset, TAP state machine]
-
A.
scopeOfUse
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
-
B.
scopeOfContribution
Indicates the specific area, domain, or extent within which an entity’s contribution or involvement applies.
-
C.
operationalScope
Indicates the range, extent, or boundaries within which an entity, process, or activity is authorized or designed to operate.
-
D.
scopeOfRecipients
Indicates the range or group of recipients to whom something (such as information, communication, or benefits) is directed or applicable.
-
E.
focusPeriod
Indicates the specific time span during which attention, activity, or analysis is concentrated on something.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2af1388190b93235602ace679e |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.