Triple
T29393894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norwich–Cromer–Sheringham railway route |
E745441
|
entity |
| Predicate | hasMarketingDesignation |
P167911
|
FINISHED |
| Object | community rail line |
—
|
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: community rail line | Statement: [Norwich–Cromer–Sheringham railway route, hasMarketingDesignation, community rail line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketingDesignation Context triple: [Norwich–Cromer–Sheringham railway route, hasMarketingDesignation, community rail line]
-
A.
hasDesignation
Indicates that an entity holds or is assigned a specific title, label, or formal designation.
-
B.
hasIspDesignation
Indicates that an entity has been assigned a specific Internet Service Provider (ISP) designation or classification.
-
C.
hasInternalDesignationFor
Indicates that one entity assigns or uses an internal label, code, or designation to refer to another entity.
-
D.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
E.
marketDesignation
chosen
Indicates that an entity has been assigned a specific market classification or label for commercial or regulatory purposes.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69ff3b32ee148190a3ba3b7600943fef |
completed | May 9, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69ff3a238af88190a2c2245e30299e48 |
completed | May 9, 2026, 1:44 p.m. |
Created at: April 28, 2026, 2:44 p.m.