Triple
T5278631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leeds Trinity University |
E119434
|
entity |
| Predicate | hasQualityFocus |
P31
|
FINISHED |
| Object | student support |
—
|
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: student support | Statement: [Leeds Trinity University, hasQualityFocus, student support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQualityFocus Context triple: [Leeds Trinity University, hasQualityFocus, student support]
-
A.
hasCoverageFocus
Indicates that one entity’s coverage, attention, or analysis is specifically focused on or directed toward another entity.
-
B.
hasQualityCriterion
Indicates that something is associated with a specific standard or criterion used to judge its quality.
-
C.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
D.
hasSurfaceQuality
Indicates that one entity possesses a particular characteristic or condition of its surface.
-
E.
hasConcentration
Indicates that one entity possesses or exhibits a specific level, strength, or density of another substance, property, or attribute.
- 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_69bd446d05a8819092ad333a3f9c8d5c |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8c9c72b08190947b6b955ac1bb5a |
completed | March 20, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69bd844a56b48190ad743c42246e02dd |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:51 p.m.