Triple
T57136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honorary Dame Commander of the Order of the British Empire (via Melinda French Gates) |
E1129
|
entity |
| Predicate | conveysPeerage |
P2803
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Honorary Dame Commander of the Order of the British Empire (via Melinda French Gates), conveysPeerage, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conveysPeerage Context triple: [Honorary Dame Commander of the Order of the British Empire (via Melinda French Gates), conveysPeerage, false]
-
A.
hereditaryPeerage
Indicates that a person holds a noble title that is legally inheritable and passes down through family lineage.
-
B.
regionOfPeerage
Indicates the geographic region or territorial area associated with a particular peerage title or rank.
-
C.
associatedNobleTitle
Indicates that an entity is linked to or bears a particular noble or aristocratic title.
-
D.
confersKnighthood
Indicates that one entity formally grants the status or title of knighthood to another entity.
-
E.
isOrderOfKnighthood
Indicates that an entity is a formal chivalric or knightly order to which individuals can be admitted.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b915c9881908c798f4dacb39f1d |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac6799c8190b508933acc0a4c7d |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b90ab24819085478dbe95f717dd |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.