Triple
T270645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telnet |
E5624
|
entity |
| Predicate | sessionOrientation |
P9934
|
FINISHED |
| Object | full-duplex |
—
|
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: full-duplex | Statement: [Telnet, sessionOrientation, full-duplex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sessionOrientation Context triple: [Telnet, sessionOrientation, full-duplex]
-
A.
supportsInternationalOrientation
Indicates that one entity facilitates, promotes, or enables the international focus, outlook, or activities of another entity.
-
B.
orientation
Indicates the relative directional alignment or facing of one entity with respect to another or to a reference frame.
-
C.
hasStripeOrientation
Indicates the directional arrangement or alignment of stripes present on an entity.
-
D.
rotationType
Indicates the specific kind or mode of rotational movement or orientation applied in a given context.
-
E.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25e69a9248190b9e7959b43223baa |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b721180819080d43c43fcbccf87 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25e68f0408190bfc851c32d6eebf3 |
completed | Feb. 28, 2026, 3:18 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.