Triple
T22266378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DfT category E station |
E550361
|
entity |
| Predicate | typicalStaffing |
P98903
|
FINISHED |
| Object | unstaffed |
—
|
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: unstaffed | Statement: [DfT category E station, typicalStaffing, unstaffed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStaffing Context triple: [DfT category E station, typicalStaffing, unstaffed]
-
A.
staffingLevel
Indicates the degree or adequacy of personnel assigned to perform a particular function, task, or operation.
-
B.
typicalMembers
Indicates that the related entities are representative or characteristic members of a larger group, category, or class.
-
C.
typicalGroup
Indicates that the subject belongs to or represents a standard, characteristic, or commonly occurring group associated with the object.
-
D.
hasStaffingModel
chosen
Indicates that an entity is associated with or operates under a particular staffing model or staffing approach.
-
E.
typicalTeamSize
Indicates the usual or most common number of members that make up a given team.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141bc458c81909837373d749b915d |
completed | April 28, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e72ff0363081909f794d19c8a64837 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:39 p.m.