Triple
T26983097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olof Daniel Westling |
E679655
|
entity |
| Predicate | weddingCeremonyType |
P3305
|
FINISHED |
| Object | royal wedding |
—
|
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: royal wedding | Statement: [Olof Daniel Westling, weddingCeremonyType, royal wedding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weddingCeremonyType Context triple: [Olof Daniel Westling, weddingCeremonyType, royal wedding]
-
A.
ceremonyType
chosen
Indicates the specific kind or category of ceremony associated with an event or relationship.
-
B.
hasPublicCeremony
Indicates that a public ceremony is held or conducted in relation to the subject entity.
-
C.
ceremonyLocationType
Indicates the type or category of location where a ceremony takes place.
-
D.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
E.
weddingStatus
Indicates the current state or condition of an entity’s marriage or wedding (e.g., single, engaged, married, divorced).
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62157d63c819096fd1addc0b960dc |
completed | May 2, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 6:47 a.m.