Triple
T25005537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Nancy |
E625830
|
entity |
| Predicate | hasMythologicalCounterpart |
P91943
|
FINISHED |
| Object | Anansi |
—
|
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: Anansi | Statement: [Mr. Nancy, hasMythologicalCounterpart, Anansi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMythologicalCounterpart Context triple: [Mr. Nancy, hasMythologicalCounterpart, Anansi]
-
A.
hasMythologicalBasis
Indicates that something is founded on, derived from, or significantly influenced by a mythological story, figure, or tradition.
-
B.
hasMythologicalNamesake
chosen
Indicates that one entity is named after, or shares its name with, a figure or element from mythology.
-
C.
hasMythologicalFeature
Indicates that an entity possesses a characteristic, attribute, or element derived from mythology or mythological beings.
-
D.
hasMythologicalUsage
Indicates that something is used, referenced, or functions within a mythological context or tradition.
-
E.
hasMythologicalDomain
Indicates that a mythological figure, deity, or entity is associated with or rules over a particular conceptual or physical domain (such as the sea, war, or the underworld).
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 18, 2026, 6:05 a.m.