Triple
T330603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muscovy Company |
E6616
|
entity |
| Predicate | notableVoyage |
P22
|
FINISHED |
| Object | 1553 voyage of Richard Chancellor to the White Sea |
—
|
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: 1553 voyage of Richard Chancellor to the White Sea | Statement: [Muscovy Company, notableVoyage, 1553 voyage of Richard Chancellor to the White Sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableVoyage Context triple: [Muscovy Company, notableVoyage, 1553 voyage of Richard Chancellor to the White Sea]
-
A.
notableExplorer
Indicates that the subject is recognized for significant achievements or prominence in the field of exploration.
-
B.
notableTour
Indicates that an entity is recognized for having a significant or well-known tour associated with it.
-
C.
notableCamp
Indicates that an entity is a camp that is notable or significant in some recognized way (e.g., historically, culturally, or by prominence).
-
D.
notableFor
chosen
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
E.
notableShip
Indicates that there is a notable or significant ship associated with the subject entity.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eaafd1a48190a6d001af3c2a5318 |
completed | Feb. 28, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69a2e94c6d8881908239d3788c018adf |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.