Triple
T23016829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mare Crisium |
E573050
|
entity |
| Predicate | nameAdoptedInCentury |
P82334
|
FINISHED |
| Object | 17th 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: 17th century | Statement: [Mare Crisium, nameAdoptedInCentury, 17th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameAdoptedInCentury Context triple: [Mare Crisium, nameAdoptedInCentury, 17th century]
-
A.
adoptedInCentury
Indicates that something (such as a practice, idea, or object) was first adopted or came into use during a specified century.
-
B.
namedAfterCentury
Indicates that something is named after a specific century, typically reflecting that century’s time period or characteristics.
-
C.
renamedInCentury
chosen
Indicates that an entity underwent a renaming during the specified century.
-
D.
hasEponymCentury
Indicates that something is named after a person associated with a particular century.
-
E.
usedAsTownNameInCentury
Indicates that a particular name was in use as the name of a town during a specified 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e59a1c8190b8048a399a4727cb |
completed | April 29, 2026, 4:07 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:52 p.m.