Triple
T23744787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D'Alesandro family |
E586783
|
entity |
| Predicate | hasFemalePoliticalLeader |
P48170
|
FINISHED |
| Object | Nancy Pelosi |
—
|
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: Nancy Pelosi | Statement: [D'Alesandro family, hasFemalePoliticalLeader, Nancy Pelosi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFemalePoliticalLeader Context triple: [D'Alesandro family, hasFemalePoliticalLeader, Nancy Pelosi]
-
A.
hasFemaleLeader
chosen
Indicates that the subject entity is led or governed by a woman in a primary leadership role.
-
B.
hasCountryLeader
Indicates that a specified country is led or governed by a particular leader (such as a president, prime minister, or monarch).
-
C.
isFirstFemaleHolderOfOffice
Indicates that a person is the first woman ever to hold a particular office or position.
-
D.
resultedInFirstElectedFemaleHeadOfStateInAfrica
Indicates that an event, action, or circumstance led to the election of the first female head of state in Africa.
-
E.
originCountryLeader
Indicates that one entity is the political leader (e.g., head of state or government) of the country from which the other entity originates.
- 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_69e24908efb08190bf755c3a9b91f222 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bcbcc4f88190a00fceeafbfb5cfd |
completed | April 29, 2026, 8:09 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:12 p.m.