Triple
T31136916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Dmitry Laptev |
E793669
|
entity |
| Predicate | eponymCenturyOfActivity |
P132332
|
FINISHED |
| Object | 18th century |
—
|
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: 18th century | Statement: [Cape Dmitry Laptev, eponymCenturyOfActivity, 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eponymCenturyOfActivity Context triple: [Cape Dmitry Laptev, eponymCenturyOfActivity, 18th century]
-
A.
hasEponymCentury
chosen
Indicates that something is named after a person associated with a particular century.
-
B.
eponymEra
Indicates that a time period or era is named after (or defined by association with) a particular person or entity.
-
C.
eponymLifespan
Indicates the time span during which the person after whom something is named was alive.
-
D.
eponymProfession
Indicates that a person’s profession is the source of an eponym, i.e., a word or name derived from that professional role.
-
E.
notableFromCentury
Indicates that an entity is notably associated with, or best known from, a particular century.
- 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:05 p.m.