Triple
T5366461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela Vicario |
E103143
|
entity |
| Predicate | weddingType |
P8399
|
FINISHED |
| Object | arranged marriage |
—
|
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: arranged marriage | Statement: [Angela Vicario, weddingType, arranged marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weddingType Context triple: [Angela Vicario, weddingType, arranged marriage]
-
A.
marriageType
chosen
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
B.
ceremonyType
Indicates the specific kind or category of ceremony associated with an event or relationship.
-
C.
marriageCustom
Indicates a culturally recognized set of practices, rules, or traditions that govern how marriages are formed, conducted, or maintained between individuals or groups.
-
D.
hasPublicCeremony
Indicates that a public ceremony is held or conducted in relation to the subject entity.
-
E.
bride
Indicates that an entity is a woman who is getting married or has just been married in relation to a wedding event or spouse.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd8682d18c8190bbb35cc75c8a7c12 |
completed | March 20, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.