Triple
T26895669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafiki's Baobab Tree |
E677891
|
entity |
| Predicate | fictionalInhabitant |
P97696
|
FINISHED |
| Object | Rafiki |
—
|
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: Rafiki | Statement: [Rafiki's Baobab Tree, fictionalInhabitant, Rafiki]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalInhabitant Context triple: [Rafiki's Baobab Tree, fictionalInhabitant, Rafiki]
-
A.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
B.
hasFictionalInhabitants
chosen
Indicates that a place or setting is inhabited by fictional or imaginary beings.
-
C.
fictionalEntityType
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
-
D.
fictionalObject
Indicates that one entity is a fictional or imaginary object in relation to another entity.
-
E.
neighborOfFictional
Indicates that one fictional entity is located next to or in close proximity to another fictional entity within a narrative or imagined setting.
- 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_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 5:47 a.m.