Triple
T984491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorothy Gale |
E21247
|
entity |
| Predicate | settingOfOrigin |
P3743
|
FINISHED |
| Object | rural Kansas |
—
|
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: rural Kansas | Statement: [Dorothy Gale, settingOfOrigin, rural Kansas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfOrigin Context triple: [Dorothy Gale, settingOfOrigin, rural Kansas]
-
A.
placeOfOrigin
chosen
Indicates the location or source from which an entity originally comes or was created.
-
B.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
C.
countryOfSetting
Indicates the country in which the setting or context of something (such as a story, event, or work) takes place.
-
D.
chamberOfOrigin
Indicates the anatomical chamber or compartment from which something (such as a structure, substance, or process) originates.
-
E.
cityOfOriginal
Indicates the city from which something or someone originally comes or was first created or established.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2aa219081908a6b0ef786b4aa52 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.