Triple
T37918777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Blue House |
E945896
|
entity |
| Predicate | hasImaginaryWorldElement |
P141333
|
FINISHED |
| Object | talking moon |
—
|
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: talking moon | Statement: [Big Blue House, hasImaginaryWorldElement, talking moon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImaginaryWorldElement Context triple: [Big Blue House, hasImaginaryWorldElement, talking moon]
-
A.
imaginaryWorld
Indicates a relationship where an entity exists within, belongs to, or is associated with a fictional or imagined world rather than the real one.
-
B.
hasImaginaryPlay
Indicates that an entity engages in or participates in pretend or imaginative play activities.
-
C.
hasImaginaryCharacter
chosen
Indicates that an entity includes, features, or is associated with a fictional or imaginary character.
-
D.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
-
E.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
- 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 3, 2026, 4:20 p.m.