Triple
T26897071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elsa’s coronation |
E677923
|
entity |
| Predicate | locationFictionalUniverse |
P26457
|
FINISHED |
| Object | Frozen franchise |
—
|
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: Frozen franchise | Statement: [Elsa’s coronation, locationFictionalUniverse, Frozen franchise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationFictionalUniverse Context triple: [Elsa’s coronation, locationFictionalUniverse, Frozen franchise]
-
A.
fictionalUniverseLocation
chosen
Indicates that one entity is a location or setting within the fictional universe to which the other entity belongs or in which it takes place.
-
B.
basedInFictionalSetting
Indicates that an entity’s primary location or setting exists within a fictional or imaginary world rather than the real world.
-
C.
stateOfFictionalLocation
Indicates that a fictional location is situated within or belongs to a particular state or state-like administrative region.
-
D.
basedInFictionalWorkLocation
Indicates that an entity’s location or setting is situated within a fictional place as depicted in a specific creative work.
-
E.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
Created at: April 27, 2026, 5:48 a.m.