Triple
T12515300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-record |
E299177
|
entity |
| Predicate | S7Meaning |
P105382
|
FINISHED |
| Object | termination record with 32-bit start address |
—
|
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: termination record with 32-bit start address | Statement: [S-record, S7Meaning, termination record with 32-bit start address]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: S7Meaning Context triple: [S-record, S7Meaning, termination record with 32-bit start address]
-
A.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
B.
meaningInGerman
Indicates that one entity expresses the meaning or translation of another entity in the German language.
-
C.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
D.
CISMeaning
Indicates that one concept, term, or symbol conveys, expresses, or stands for a particular meaning or interpretation in a given context.
-
E.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954b715fc819091fa84430be46273 |
completed | April 10, 2026, 7:51 p.m. |
Created at: April 8, 2026, 9:57 p.m.