Triple
T25465953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the Smile |
E638171
|
entity |
| Predicate | hasTitleForRecipients |
P69419
|
FINISHED |
| Object | Knight of the Order of the Smile |
—
|
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: Knight of the Order of the Smile | Statement: [Order of the Smile, hasTitleForRecipients, Knight of the Order of the Smile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleForRecipients Context triple: [Order of the Smile, hasTitleForRecipients, Knight of the Order of the Smile]
-
A.
recipientTitleUsage
Indicates how a title or honorific is used when addressing or referring to the recipient in the context of the relationship or action.
-
B.
hasTitleIn
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
-
C.
hasTitleFrom
chosen
Indicates that one entity holds or uses a title that originates from, or is conferred by, another entity.
-
D.
hasReceivedTitle
Indicates that an entity has been granted or awarded a specific title or honor.
-
E.
hasTitleName
Indicates that an entity possesses or is associated with a specific title or name.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 2:14 p.m.