Triple
T28536672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen (The Snows of Kilimanjaro) |
E722180
|
entity |
| Predicate | settingWithCharacter |
P90820
|
FINISHED |
| Object | Africa |
—
|
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: Africa | Statement: [Helen (The Snows of Kilimanjaro), settingWithCharacter, Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingWithCharacter Context triple: [Helen (The Snows of Kilimanjaro), settingWithCharacter, Africa]
-
A.
characterSetStorage
Indicates that a particular character set is used for storing data in a given context or system.
-
B.
characterSetOrigin
Indicates the source or defining system from which a particular character set is derived or specified.
-
C.
characterSetting
chosen
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
-
D.
usesCharactersAs
Indicates that one entity employs or incorporates specific characters (such as letters, symbols, or glyphs) from another entity for its representation or functioning.
-
E.
characterSetType
Indicates the type or category of character set associated with or used by an 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_69f01a5d7ec88190ada2d5be7c06c35d |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 28, 2026, 3:32 a.m.