Triple
T28434953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telnet Timing Mark Option |
E715236
|
entity |
| Predicate | insertsInto |
P23133
|
FINISHED |
| Object | Telnet data stream |
—
|
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: Telnet data stream | Statement: [Telnet Timing Mark Option, insertsInto, Telnet data stream]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: insertsInto Context triple: [Telnet Timing Mark Option, insertsInto, Telnet data stream]
-
A.
injectsInto
chosen
Indicates that one entity introduces or forces a substance or element into another entity, typically via a directed flow or insertion process.
-
B.
insertedUnder
Indicates that one entity has been placed or positioned beneath another entity, typically in a physical or structural context.
-
C.
setInto
Indicates placing or inserting one entity into another entity or context, often initiating a new state or condition.
-
D.
mergedInto
Indicates that one entity has been combined with and absorbed into another entity, ceasing to exist as a separate unit.
-
E.
insertionManeuver
Indicates the action of placing or guiding one object or component into another or into a designated position.
- 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_69efd6b253888190b3c7222ed6a403a8 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64e391974819085b2c505fdb804f3 |
completed | May 2, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 1:42 a.m.