Triple
T36029249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Jude’s School for Boys |
E1042211
|
entity |
| Predicate | hasNotableAlumnusFictional |
P82963
|
FINISHED |
| Object | Chuck Bass |
E311591
|
NE 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: Chuck Bass | Statement: [St. Jude’s School for Boys, hasNotableAlumnusFictional, Chuck Bass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAlumnusFictional Context triple: [St. Jude’s School for Boys, hasNotableAlumnusFictional, Chuck Bass]
-
A.
hasNotableTeacherFictional
Indicates that a fictional entity has a notable teacher within a narrative or fictional context.
-
B.
hasNotableResidentInFiction
Indicates that a place or entity is notably associated with a fictional character who is depicted as residing there.
-
C.
hasNotableAlumniType
Indicates that an entity has notable alumni belonging to a specified category or type.
-
D.
hasNotableAlumniInstitution
chosen
Indicates that an institution is associated with one or more notable alumni who previously attended or graduated from it.
-
E.
hasFictionalLeadCharacter
Indicates that a creative work features a particular fictional character as its main or leading protagonist.
- F. None of above.
Provenance (4 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_69f76e2c568881909e1e21f85252b0f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a394d1e1ad881908635115d8f109997 |
completed | June 22, 2026, 2:56 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.