Triple
T32626088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IC trains to Charleroi |
E834059
|
entity |
| Predicate | categoryWithinNetwork |
P99471
|
FINISHED |
| Object | IC (InterCity) category |
—
|
NE NERFINISHED |
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: IC (InterCity) category | Statement: [IC trains to Charleroi, categoryWithinNetwork, IC (InterCity) category]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categoryWithinNetwork Context triple: [IC trains to Charleroi, categoryWithinNetwork, IC (InterCity) category]
-
A.
categoryWithinOrganization
Indicates that one organizational unit or category is contained within, and hierarchically belongs to, a broader organizational structure.
-
B.
inNetwork
Indicates that one entity is within the same defined network, system, or coverage group as another entity, such that network-based interactions or benefits apply between them.
-
C.
groupWithin
Indicates that one group is contained or nested as a subgroup within another, larger group.
-
D.
networkCategory
chosen
Indicates the classification or type of network to which an entity or connection belongs.
-
E.
hasRoleInNetwork
Indicates that an entity holds a specific functional position or responsibility within a particular network.
- 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_69f3492ccc80819086ef7d26e9786647 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cd126fcc8190aa1f1f146e45ec0c |
completed | May 3, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:06 a.m.