Triple
T2908684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American College of Switzerland |
E63628
|
entity |
| Predicate | alumniNotabilityField |
P39276
|
FINISHED |
| Object | cinema |
—
|
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: cinema | Statement: [American College of Switzerland, alumniNotabilityField, cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alumniNotabilityField Context triple: [American College of Switzerland, alumniNotabilityField, cinema]
-
A.
notableField
chosen
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
B.
notableStudentOrColleague
Indicates that one entity is a notable student or professional colleague of another entity.
-
C.
notableStudent
Indicates that a person is a distinguished or particularly significant student of another individual or institution.
-
D.
notableFieldOfRecipients
Indicates that the recipients are notable or recognized specifically in a particular field or area of expertise.
-
E.
hasNotableAlumniType
Indicates that an entity has notable alumni belonging to a specified category or type.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0d329c88190b6fcaef0be1799eb |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd19bac881908f047d616aca8438 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:11 p.m.