Triple
T11713203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josephine Baker |
E278422
|
entity |
| Predicate | adoptedChildrenFrom |
P100919
|
FINISHED |
| Object | multiple countries |
—
|
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: multiple countries | Statement: [Josephine Baker, adoptedChildrenFrom, multiple countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adoptedChildrenFrom Context triple: [Josephine Baker, adoptedChildrenFrom, multiple countries]
-
A.
adoptedChildren
Indicates that one entity has legally taken another entity as their child through adoption.
-
B.
numberOfAdoptedChildren
Indicates the count of children that an entity has legally adopted.
-
C.
adoptedWith
Indicates that two or more entities were adopted at the same time or as part of the same adoption event or process.
-
D.
adoptedAs
Indicates that one entity has taken another into its family or care through a formal or recognized adoption process.
-
E.
adoptedUnder
Indicates that something has been formally accepted, implemented, or brought into effect according to a specified rule, procedure, or authority.
- F. None of above. chosen
Provenance (4 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4be10088190854699385d1f6a95 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:40 p.m.