Triple
T30573319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prospekt Vernadskogo |
E778174
|
entity |
| Predicate | namedAfterFieldOfEponym |
P117207
|
FINISHED |
| Object | geochemistry |
—
|
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: geochemistry | Statement: [Prospekt Vernadskogo, namedAfterFieldOfEponym, geochemistry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterFieldOfEponym Context triple: [Prospekt Vernadskogo, namedAfterFieldOfEponym, geochemistry]
-
A.
fieldOfEponym
chosen
Indicates the domain, discipline, or area of activity in which an eponymous name (e.g., a person or thing something is named after) is recognized or relevant.
-
B.
eponymProfession
Indicates that a person’s profession is the source of an eponym, i.e., a word or name derived from that professional role.
-
C.
eponymKnownFor
Indicates that a person or entity is widely recognized or named as the source or inspiration for something else (such as a concept, place, or object).
-
D.
peopleNamedAfter
Indicates that one person or group received their name in honor of, or derived from, another person or group.
-
E.
hasNamedAfterPerson
Indicates that one entity is named in honor of, or derived from the name of, a specific person.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 29, 2026, 8:22 p.m.