Triple
T38318950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of Theresa |
E1036603
|
entity |
| Predicate | chivalricOrderCategory |
P190638
|
FINISHED |
| Object | women’s order |
—
|
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: women’s order | Statement: [Order of Theresa, chivalricOrderCategory, women’s order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chivalricOrderCategory Context triple: [Order of Theresa, chivalricOrderCategory, women’s order]
-
A.
isOrderOfKnighthood
Indicates that an entity is a formal chivalric or knightly order to which individuals can be admitted.
-
B.
associatedWithNobleOrder
Indicates that an entity has a formal or recognized connection to a noble order, such as membership, affiliation, or honorary association.
-
C.
chivalricTradition
Indicates a relationship where behaviors, values, or actions conform to or are guided by the codes and ideals of chivalry.
-
D.
countryOfKnighthood
Indicates the country in which an individual was granted a knighthood.
-
E.
rankInLegionOfHonour
Indicates the specific level or grade a person holds within the hierarchy of the Legion of Honour distinction.
- F. None of above. chosen
Provenance (4 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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
| PDg | Predicate description generation | batch_69fccbd6b7688190b746803cf78d5704 |
completed | May 7, 2026, 5:28 p.m. |
Created at: May 3, 2026, 4:30 p.m.