Triple
T11910210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S7 stock (DLR type) |
E283372
|
entity |
| Predicate | hasServicePatternType |
P849
|
FINISHED |
| Object | high frequency metro service |
—
|
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: high frequency metro service | Statement: [S7 stock (DLR type), hasServicePatternType, high frequency metro service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServicePatternType Context triple: [S7 stock (DLR type), hasServicePatternType, high frequency metro service]
-
A.
hasServicePatternRole
Indicates that an entity participates in a service pattern with a specific functional role or responsibility within that pattern.
-
B.
hasServicePatternNote
Indicates that a service pattern (such as a schedule or routing pattern) is associated with a specific explanatory note or annotation.
-
C.
hasRegularServicePattern
Indicates that an entity consistently follows a defined, recurring schedule or pattern of service over time.
-
D.
hasServiceType
chosen
Indicates that an entity is associated with or categorized by a particular type of service.
-
E.
hasServicePatternChange
Indicates that there is a modification in the usual or scheduled pattern of a service’s operation.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e5278eb081909a7ecfe38beeeda9 |
completed | April 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_69d8bb3632ac8190b13e53c2b5db7125 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.