Triple
T35385713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Methuen Home for Girls |
E1022786
|
entity |
| Predicate | hasStaffMemberInFiction |
P61558
|
FINISHED |
| Object | Mr. Shaibel |
—
|
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: Mr. Shaibel | Statement: [Methuen Home for Girls, hasStaffMemberInFiction, Mr. Shaibel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffMemberInFiction Context triple: [Methuen Home for Girls, hasStaffMemberInFiction, Mr. Shaibel]
-
A.
hasFictionalStaffMember
chosen
Indicates that an entity includes or employs a staff member who is a fictional character.
-
B.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
-
C.
hasFictionalMember
Indicates that a group, organization, or collection includes at least one member that is fictional rather than real.
-
D.
hasFictionalEditor
Indicates that an entity is associated with a fictional editor character responsible for editing or overseeing its content within a narrative or fictional context.
-
E.
hasRankInFiction
Indicates that a fictional character or entity holds a specific rank, title, or hierarchical position within a fictional context or universe.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffebbd9bac8190b3dca4b7252a2278 |
completed | May 10, 2026, 2:21 a.m. |
| PD | Predicate disambiguation | batch_69ffe93120a08190a44bb64d052eda78 |
completed | May 10, 2026, 2:10 a.m. |
Created at: May 3, 2026, 4:03 p.m.