Triple
T24412859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knight Grand Cross |
E615500
|
entity |
| Predicate | isMaleEquivalentOf |
P15994
|
FINISHED |
| Object | Dame Grand Cross |
—
|
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: Dame Grand Cross | Statement: [Knight Grand Cross, isMaleEquivalentOf, Dame Grand Cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMaleEquivalentOf Context triple: [Knight Grand Cross, isMaleEquivalentOf, Dame Grand Cross]
-
A.
maleEquivalent
chosen
Indicates that one entity is the corresponding male counterpart or equivalent of another entity.
-
B.
hasFemaleEquivalent
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
C.
hasFemaleFormOf
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
-
D.
genderOfEponym
Indicates the gender of the person after whom something (such as a place, object, or concept) is named.
-
E.
isUnisexVariantOf
Indicates that one item is a gender-neutral or unisex version or form of another item.
- 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_69e2d7e9bfac8190a748952a90957106 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2958302ec8190bf32409a5ca00ebf |
completed | April 29, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:11 a.m.