Triple
T15120049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DfT category E |
E361145
|
entity |
| Predicate | typicalStaffingLevel |
P63143
|
FINISHED |
| Object | unstaffed or lightly staffed |
—
|
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 or lightly staffed | Statement: [DfT category E, typicalStaffingLevel, unstaffed or lightly staffed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStaffingLevel Context triple: [DfT category E, typicalStaffingLevel, unstaffed or lightly staffed]
-
A.
staffingLevel
chosen
Indicates the degree or adequacy of personnel assigned to perform a particular function, task, or operation.
-
B.
typicalSeniorityLevel
Indicates the usual or most common rank or seniority level associated with an entity in a given context.
-
C.
typicalHighestLevel
Indicates the usual or most common maximum level or degree that something typically reaches within a given context.
-
D.
typicalEquipmentLevel
Indicates the usual or standard amount or quality of equipment associated with an entity or situation.
-
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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0059e036c8190959ff3bde8f2356f |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:06 a.m.