Triple
T10168324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noise_XK pattern |
E235262
|
entity |
| Predicate | letterKMeaning |
P47684
|
FINISHED |
| Object | responder static key known to initiator |
—
|
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: responder static key known to initiator | Statement: [Noise_XK pattern, letterKMeaning, responder static key known to initiator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: letterKMeaning Context triple: [Noise_XK pattern, letterKMeaning, responder static key known to initiator]
-
A.
letterMeaning
chosen
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
B.
lettersMeaning
Indicates that a set of letters or characters represents, signifies, or conveys a particular meaning or message.
-
C.
chantMeaning
Indicates that an entity performs or conveys the meaning or content of a chant in relation to another entity or context.
-
D.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
E.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6f64a48190883aefce58a65ca6 |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.