Triple
T28676656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doppler (lunar crater) |
E725885
|
entity |
| Predicate | hasEponymKnownFor |
P56375
|
FINISHED |
| Object | Doppler effect |
—
|
NE NERFINISHED |
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: Doppler effect | Statement: [Doppler (lunar crater), hasEponymKnownFor, Doppler effect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEponymKnownFor Context triple: [Doppler (lunar crater), hasEponymKnownFor, Doppler effect]
-
A.
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).
-
B.
hasEponymConnectionTo
chosen
Indicates that one entity is named after, derived from, or otherwise linguistically or honorifically connected to another entity as its eponym.
-
C.
hasEponymCategory
Indicates that one entity serves as the namesake or eponym for the category or class represented by the other entity.
-
D.
hasEponymCauseOfDeath
Indicates that an entity’s cause of death is named after (or eponymously derived from) a particular person or entity.
-
E.
eponymProfession
Indicates that a person’s profession is the source of an eponym, i.e., a word or name derived from that professional role.
- 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_69f01d867608819086bc3e6b4f9de866 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65634ec1481908dadc84711b47ae6 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 5:06 a.m.