Triple
T4227087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curaray River |
E94483
|
entity |
| Predicate | hasHistoricalEventType |
P2107
|
FINISHED |
| Object | missionary activity |
—
|
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: missionary activity | Statement: [Curaray River, hasHistoricalEventType, missionary activity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalEventType Context triple: [Curaray River, hasHistoricalEventType, missionary activity]
-
A.
hasHistoricalEvent
chosen
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
B.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
-
C.
hasHistoricMarker
Indicates that something is associated with or identified by an official historic marker or plaque recognizing its historical significance.
-
D.
hasTypeHistory
Indicates that an entity is associated with a record or sequence of its past and present types or classifications over time.
-
E.
hasHistoricalSection
Indicates that something includes a dedicated part or segment that presents historical information or context.
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e5003008190834726e46df3ee9b |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.