Triple
T23736404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Consultative Assembly of Saudi Arabia |
E586551
|
entity |
| Predicate | firstWomenMembersAdmitted |
P48982
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [Consultative Assembly of Saudi Arabia, firstWomenMembersAdmitted, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstWomenMembersAdmitted Context triple: [Consultative Assembly of Saudi Arabia, firstWomenMembersAdmitted, 2013]
-
A.
admittedWomen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
-
B.
firstWomenAwarded
Indicates that the subject is the first woman to have received the specified award.
-
C.
womenSuffrageGrantedIn
Indicates that women were granted the legal right to vote in a specified place or jurisdiction.
-
D.
hasFirstLadyMember
Indicates that an entity has, as a member, a woman who holds the role or title of First Lady.
-
E.
firstFemaleHolderDate
chosen
Indicates the date on which the first female individual came to hold a given position, title, or role.
- 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_69e24907dc9c8190be074c9c96a0ec2d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bad28fa481909d7a6a6e98a7b0a5 |
completed | April 29, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:10 p.m.