Triple
T8933321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unity Party (Liberia) |
E212709
|
entity |
| Predicate | hasGenderMilestone |
P86266
|
FINISHED |
| Object | first elected female head of state in Africa through Ellen Johnson Sirleaf |
—
|
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: first elected female head of state in Africa through Ellen Johnson Sirleaf | Statement: [Unity Party (Liberia), hasGenderMilestone, first elected female head of state in Africa through Ellen Johnson Sirleaf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderMilestone Context triple: [Unity Party (Liberia), hasGenderMilestone, first elected female head of state in Africa through Ellen Johnson Sirleaf]
-
A.
genderMilestone
Indicates a significant event or transition related to an entity’s gender identity, status, or recognition.
-
B.
hadGender
Indicates that an entity possessed a specific gender.
-
C.
hasGenderHistory
Indicates that an entity has undergone or experienced a change or transition in gender over time.
-
D.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
E.
hasIncarnationsOfGender
Indicates that an entity has different incarnations or forms that each express or are associated with a particular gender.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668fa87c8190bfeda820368b89e4 |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
| PDg | Predicate description generation | batch_69cc608331f88190bcb500ff63527f8a |
completed | April 1, 2026, 12:02 a.m. |
Created at: March 30, 2026, 6:57 p.m.