Triple
T9060740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drosselmeier |
E217113
|
entity |
| Predicate | hasRelationshipToNutcracker |
P86155
|
FINISHED |
| Object | giver of the nutcracker |
—
|
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: giver of the nutcracker | Statement: [Drosselmeier, hasRelationshipToNutcracker, giver of the nutcracker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipToNutcracker Context triple: [Drosselmeier, hasRelationshipToNutcracker, giver of the nutcracker]
-
A.
hasBalletMaster
Indicates that an entity is associated with or overseen by a specific ballet master responsible for its ballet-related training, direction, or instruction.
-
B.
hasDanceChoreography
Indicates that an entity is associated with or characterized by a specific dance choreography.
-
C.
hasRelationshipToJackTorrance
Indicates that one entity has some form of relationship or connection to Jack Torrance.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
- F. None of above. chosen
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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7ecbb1e88190acdbfccdd975fac1 |
completed | April 1, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee6d83c819095d8ed0779aa8511 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f4f1cb48190a025d1b3d8d7a790 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:11 p.m.