Triple
T19284650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humphrey Van Weyden |
E482278
|
entity |
| Predicate | shipTypeEncountered |
P114106
|
FINISHED |
| Object | sealing schooner |
—
|
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: sealing schooner | Statement: [Humphrey Van Weyden, shipTypeEncountered, sealing schooner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipTypeEncountered Context triple: [Humphrey Van Weyden, shipTypeEncountered, sealing schooner]
-
A.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
B.
encountersShip
Indicates that one entity comes across or meets another ship, typically in the course of travel or movement.
-
C.
shipInvolved
Indicates that a ship participates in, is associated with, or plays a role in a specified event or situation.
-
D.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
E.
vesselTypeServedOn
chosen
Indicates the type of vessel on which an entity has served or performed duty.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc0152d48190b92272d4c7caa708 |
completed | April 20, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:30 p.m.