Triple
T26399006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Label Distribution Protocol |
E663648
|
entity |
| Predicate | tLDPUsedFor |
P160502
|
FINISHED |
| Object | non-directly connected LSRs |
—
|
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: non-directly connected LSRs | Statement: [Label Distribution Protocol, tLDPUsedFor, non-directly connected LSRs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tLDPUsedFor Context triple: [Label Distribution Protocol, tLDPUsedFor, non-directly connected LSRs]
-
A.
usedAsL2By
Indicates that something serves as a second language (L2) for a particular user or group of users.
-
B.
L2Is
Indicates that one entity is located at or occupies a specific level 2 (L2) position or layer relative to another entity.
-
C.
laterUsedBy
Indicates that something is subsequently utilized or employed by a specified entity at a later time.
-
D.
tunnelUse
Indicates that one entity makes use of or passes through a tunnel associated with another entity.
-
E.
tdp
Indicates a temporal dependency or precedence relation where one event or process must occur before or in coordination with another.
- 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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610f2c09c8190849494490f255758 |
completed | May 2, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f5f800fa9c8190aab0962669fde8ac |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f6018ceb1c8190a6a5f84071659a96 |
completed | May 2, 2026, 1:52 p.m. |
Created at: April 26, 2026, 11:30 p.m.