Triple
T19683882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Line (Auckland) |
E472661
|
entity |
| Predicate | hasPeakServicePattern |
P136908
|
FINISHED |
| Object | higher frequency during weekday peaks |
—
|
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: higher frequency during weekday peaks | Statement: [Eastern Line (Auckland), hasPeakServicePattern, higher frequency during weekday peaks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPeakServicePattern Context triple: [Eastern Line (Auckland), hasPeakServicePattern, higher frequency during weekday peaks]
-
A.
hasPeakServiceType
Indicates that an entity is associated with a specific type or category of service provided during peak periods.
-
B.
hasPeakDirectionService
Indicates that a transportation service operates primarily or exclusively in a specified direction during peak travel periods.
-
C.
hasRegularServicePattern
Indicates that an entity consistently follows a defined, recurring schedule or pattern of service over time.
-
D.
hasPeak
Indicates that something possesses or contains a highest point, summit, or maximum value.
-
E.
hasPeakCount
Indicates the number of distinct peaks associated with an entity.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e641c225fc81909637d304891f4abd |
completed | April 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69e53039ea808190a9106a53f564ab92 |
completed | April 19, 2026, 7:42 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:45 p.m.