Triple
T29924737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louise Arner Boyd’s European expeditions |
E760045
|
entity |
| Predicate | hasGenderOfLeader |
P48170
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [Louise Arner Boyd’s European expeditions, hasGenderOfLeader, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderOfLeader Context triple: [Louise Arner Boyd’s European expeditions, hasGenderOfLeader, female]
-
A.
hasFemaleLeader
chosen
Indicates that the subject entity is led or governed by a woman in a primary leadership role.
-
B.
genderOfMostOfficeHolders
Indicates the predominant gender among individuals who hold most of the offices or positions within a given group or organization.
-
C.
hasCountryLeader
Indicates that a specified country is led or governed by a particular leader (such as a president, prime minister, or monarch).
-
D.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
E.
officeHoldersGenderEligibility
Indicates the gender-based criteria that determine who is eligible to hold a particular office or position.
- 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_69f224631674819080c8d089674f9f4f |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 29, 2026, 6:15 p.m.