Triple
T9158265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guanahani |
E219758
|
entity |
| Predicate | voyageNumberOfColumbusLanding |
P18374
|
FINISHED |
| Object | first voyage |
—
|
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: first voyage | Statement: [Guanahani, voyageNumberOfColumbusLanding, first voyage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voyageNumberOfColumbusLanding Context triple: [Guanahani, voyageNumberOfColumbusLanding, first voyage]
-
A.
numberOfVoyagesToAmericas
Indicates the count of distinct voyages an entity has made to the Americas.
-
B.
sponsorshipYearColumbusFirstVoyage
Indicates the year in which sponsorship was provided for Columbus’s first voyage.
-
C.
firstVoyageEndYear
Indicates the calendar year in which an entity’s first voyage or initial journey was completed or came to an end.
-
D.
yearOfEuropeanExploration
Indicates the specific year in which a European exploration of the referenced entity took place.
-
E.
firstVoyageDestination
chosen
Indicates the location that an entity traveled to as the endpoint of its first voyage.
- 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_69ca83e25418819093c6503deeaf30de |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca9d6b9ac819094efe12c1ed67ecf |
completed | April 1, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69cc6605c6808190a30d92da006206ac |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:21 p.m.