Triple
T19052269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoher Orden vom Schwarzen Adler |
E466288
|
entity |
| Predicate | allowedFemaleMembers |
P12173
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hoher Orden vom Schwarzen Adler, allowedFemaleMembers, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowedFemaleMembers Context triple: [Hoher Orden vom Schwarzen Adler, allowedFemaleMembers, yes]
-
A.
hadFemaleMembers
Indicates that the subject group or organization included one or more female individuals among its members.
-
B.
memberCountFemale
Indicates the number of female members associated with a given group or entity.
-
C.
genderOfMembers
Indicates the gender or genders associated with the members of a group or organization.
-
D.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
E.
admittedWomen
chosen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc031ff881908e8c68c7aaff3733 |
completed | April 20, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.