Triple
T4292572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newcastle Transport |
E99629
|
entity |
| Predicate | serviceFrequencyType |
P55256
|
FINISHED |
| Object | timetabled services |
—
|
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: timetabled services | Statement: [Newcastle Transport, serviceFrequencyType, timetabled services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceFrequencyType Context triple: [Newcastle Transport, serviceFrequencyType, timetabled services]
-
A.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
B.
meetingFrequency
Indicates how often a meeting or recurring gathering takes place over a given period.
-
C.
laterFrequency
Indicates that one event, state, or action occurs with a lower frequency than another in a temporal sequence.
-
D.
rotationPeriod_hours
Indicates the length of time, measured in hours, that an object takes to complete one full rotation on its axis.
-
E.
typicalFrequencyUnit
Indicates the unit of measurement typically used to express the frequency of an event, action, or occurrence.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3508035a08190b752c8edce0aff86 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:08 p.m.