Triple
T5480564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BGCF |
E123456
|
entity |
| Predicate | routesFrom |
P64267
|
FINISHED |
| Object | IP-based multimedia networks |
—
|
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: IP-based multimedia networks | Statement: [BGCF, routesFrom, IP-based multimedia networks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routesFrom Context triple: [BGCF, routesFrom, IP-based multimedia networks]
-
A.
routeBetween
Indicates that there exists a path or connection enabling travel or communication between two locations or points.
-
B.
routeVia
Indicates that a connection, path, or communication between two points is established or carried out through an intermediate location, node, or channel.
-
C.
numberOfRoutes
Indicates the total count of distinct routes or paths associated with a given entity or between specified entities.
-
D.
routeOptimization
Indicates the process of determining the most efficient path or sequence of paths between locations according to specified criteria such as distance, time, or cost.
-
E.
routeDescription
Indicates a textual explanation or summary of the path, course, or itinerary taken between locations.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd93e5d0f08190a6cc9fc408b7c5bb |
completed | March 20, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69bd91a73b148190a865243536a4fe76 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd93e4d2d081908eb75ee22fe72824 |
completed | March 20, 2026, 6:37 p.m. |
Created at: March 20, 2026, 2:09 p.m.