Triple
T4045574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Oversteek |
E84056
|
entity |
| Predicate | hasLightingRitualTime |
P53783
|
FINISHED |
| Object | sunset |
—
|
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: sunset | Statement: [De Oversteek, hasLightingRitualTime, sunset]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightingRitualTime Context triple: [De Oversteek, hasLightingRitualTime, sunset]
-
A.
hasRitual
Indicates that an entity performs, observes, or is associated with a specific ritual or ceremonial practice.
-
B.
hasRitualCalendar
Indicates that an entity maintains or is associated with a structured schedule of ritual or ceremonial events.
-
C.
hasRitualObject
Indicates that an entity possesses, uses, or is associated with an object specifically employed in a ritual or ceremonial context.
-
D.
hasRitualSpace
Indicates that an entity possesses or is associated with a designated space used for ritual or ceremonial activities.
-
E.
hasRitualContext
Indicates that one entity is associated with, or occurs within, a ritual or ceremonial context in relation to another entity.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb6135b481909d2be890a2140ff9 |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef98ed84c81909dc86097df4afd4f |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:37 p.m.