Triple
T26002183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parliament (Qualification of Women) Act 1918 |
E646658
|
entity |
| Predicate | enabledFirstWomanMPToSit |
P160705
|
FINISHED |
| Object | Nancy Astor |
—
|
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 Astor | Statement: [Parliament (Qualification of Women) Act 1918, enabledFirstWomanMPToSit, Nancy Astor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enabledFirstWomanMPToSit Context triple: [Parliament (Qualification of Women) Act 1918, enabledFirstWomanMPToSit, Nancy Astor]
-
A.
isFirstFemaleHolderOfOffice
Indicates that a person is the first woman ever to hold a particular office or position.
-
B.
firstFemaleHolderDate
Indicates the date on which the first female individual came to hold a given position, title, or role.
-
C.
countryFirstToGrantWomenVote
Indicates that the subject country was the earliest or among the earliest to legally grant women the right to vote.
-
D.
hasFirstLadyMember
Indicates that an entity has, as a member, a woman who holds the role or title of First Lady.
-
E.
hasFirstFemaleGraduate
Indicates that an institution or program has a specific person who is recognized as its first female graduate.
- 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_69e77e89d5848190b54352cdb74f6029 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605770b2481908c1674952889f62f |
completed | May 2, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f603b90c94819088d62cb9489e95ff |
completed | May 2, 2026, 2:01 p.m. |
Created at: April 22, 2026, 9 a.m.