Triple
T13512171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendy Darling |
E322665
|
entity |
| Predicate | hasImaginaryExperienceWith |
P51831
|
FINISHED |
| Object | flying |
—
|
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: flying | Statement: [Wendy Darling, hasImaginaryExperienceWith, flying]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImaginaryExperienceWith Context triple: [Wendy Darling, hasImaginaryExperienceWith, flying]
-
A.
hasImaginedIdentity
chosen
Indicates that an entity mentally constructs or adopts a non-actual identity, role, or persona for itself or another entity.
-
B.
hasVirtualExperience
Indicates that one entity possesses or has participated in a virtual or digitally simulated experience related to another entity.
-
C.
gaveFirsthandExperienceOf
Indicates that one entity directly provided another entity with personal, firsthand experience of something, rather than secondhand or indirect knowledge.
-
D.
hasHad
Indicates that an entity previously experienced, possessed, or was involved in something at some point in the past.
-
E.
hasAlternateExperience
Indicates that an entity is associated with a different or substitute experience relative to a primary or standard one.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf86a6208190be8c18f7a0158f23 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:44 p.m.