Triple
T28147640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Coat School, Dudley |
E714526
|
entity |
| Predicate | hasAlumnusTitle |
P117403
|
FINISHED |
| Object | Knight Bachelor (Sir Lenny Henry) |
—
|
NE NERFINISHED |
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: Knight Bachelor (Sir Lenny Henry) | Statement: [Blue Coat School, Dudley, hasAlumnusTitle, Knight Bachelor (Sir Lenny Henry)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlumnusTitle Context triple: [Blue Coat School, Dudley, hasAlumnusTitle, Knight Bachelor (Sir Lenny Henry)]
-
A.
hasAlumnusPosition
Indicates that an individual holds or has held a position or role as an alumnus of a particular institution or organization.
-
B.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
C.
hasAlumnusAchievement
chosen
Indicates that an alumnus has attained a specific notable achievement or distinction.
-
D.
hasAlumniField
Indicates a relationship where an entity is associated with a specific field or area of study in which its alumni specialized or graduated.
-
E.
namedAlumnus
Indicates that an entity is explicitly identified or designated as an alumnus of another entity (such as an institution or organization).
- 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_69efd6b033208190bf74f80a147e2092 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 27, 2026, 9:57 p.m.