Triple
T28808084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SLFP |
E727433
|
entity |
| Predicate | hasWomenLeaderMilestone |
P4487
|
FINISHED |
| Object | Sirimavo Bandaranaike as world’s first female prime minister |
—
|
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: Sirimavo Bandaranaike as world’s first female prime minister | Statement: [SLFP, hasWomenLeaderMilestone, Sirimavo Bandaranaike as world’s first female prime minister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWomenLeaderMilestone Context triple: [SLFP, hasWomenLeaderMilestone, Sirimavo Bandaranaike as world’s first female prime minister]
-
A.
hasFemaleLeader
Indicates that the subject entity is led or governed by a woman in a primary leadership role.
-
B.
isFirstFemaleHolderOfOffice
chosen
Indicates that a person is the first woman ever to hold a particular office or position.
-
C.
hasWomenOrganization
Indicates that an entity is associated with, contains, or is part of an organization specifically for women.
-
D.
hadWomenOrganization
Indicates that an entity was associated with or involved in an organization focused on women or women’s issues.
-
E.
hasGenderBarrierBroken
Indicates that a previously existing gender-based barrier or limitation has been overcome or removed in the given context.
- 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f7b2f3a104819098ddd8909eaf596c |
completed | May 3, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
Created at: April 28, 2026, 6:29 a.m.