Triple
T1203410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knights Companion of the Order of the Garter |
E25832
|
entity |
| Predicate | femaleEquivalentStyle |
P1613
|
FINISHED |
| Object | Lady |
—
|
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: Lady | Statement: [Knights Companion of the Order of the Garter, femaleEquivalentStyle, Lady]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleEquivalentStyle Context triple: [Knights Companion of the Order of the Garter, femaleEquivalentStyle, Lady]
-
A.
hasFemaleEquivalent
chosen
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
B.
maleEquivalent
Indicates that one entity is the corresponding male counterpart or equivalent of another entity.
-
C.
womenWing
Indicates a relationship where a woman is associated with or positioned at the wing (side section) of a structure, group, or setting.
-
D.
genderNeutralForm
Indicates that one entity is a gender-neutral linguistic form or expression corresponding to another, more gendered form.
-
E.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdbf94188190991f63a84cc76b8a |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.