Triple
T4887488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coronation of Mary |
E109472
|
entity |
| Predicate | contemplatesEvent |
P6686
|
FINISHED |
| Object | Mary crowned as Queen of Heaven and Earth |
—
|
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: Mary crowned as Queen of Heaven and Earth | Statement: [Coronation of Mary, contemplatesEvent, Mary crowned as Queen of Heaven and Earth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contemplatesEvent Context triple: [Coronation of Mary, contemplatesEvent, Mary crowned as Queen of Heaven and Earth]
-
A.
includesEvents
Indicates that one entity contains or encompasses one or more events as part of its scope or composition.
-
B.
coversEvent
Indicates that one event includes, spans, or encompasses the time period or occurrence of another event.
-
C.
eventIn
Indicates that an event occurs within, or is situated in, a specific location, context, or larger event.
-
D.
portraysEvent
chosen
Indicates that one entity depicts, represents, or illustrates a particular event.
-
E.
eventUse
Indicates that an event involves the use or utilization of a particular entity (e.g., a resource, tool, or method) as part of its occurrence.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.