Triple
T512578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancaster University |
E10638
|
entity |
| Predicate | administrativeStaff |
P12729
|
FINISHED |
| Object | over 1,000 |
—
|
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: over 1,000 | Statement: [Lancaster University, administrativeStaff, over 1,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeStaff Context triple: [Lancaster University, administrativeStaff, over 1,000]
-
A.
personnelComposition
chosen
Indicates the makeup or distribution of people or roles within a group, organization, or unit.
-
B.
administeredBy
Indicates that an action, service, or process is carried out, managed, or overseen by a specified agent or authority.
-
C.
staffIncluded
Indicates that staff members are included or provided as part of the associated entity, service, or arrangement.
-
D.
personnelType
Indicates the classification or role category assigned to a person within an organization or system.
-
E.
peakPersonnel
Indicates the maximum number of personnel involved or present at any point during a specified period or activity.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f232fa688190b08a2fe3f22c7a6e |
completed | Feb. 28, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69a2f013c05481909e6dc87e7b20ebd8 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.