Triple
T36577970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1940 Whipple |
E902308
|
entity |
| Predicate | eponymHasNotableTheory |
P55473
|
FINISHED |
| Object | icy conglomerate model of comets |
—
|
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: icy conglomerate model of comets | Statement: [1940 Whipple, eponymHasNotableTheory, icy conglomerate model of comets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eponymHasNotableTheory Context triple: [1940 Whipple, eponymHasNotableTheory, icy conglomerate model of comets]
-
A.
hasTheoremNamedAfter
Indicates that a theorem is named in honor of or after a particular person or entity.
-
B.
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).
-
C.
eponymProfession
Indicates that a person’s profession is the source of an eponym, i.e., a word or name derived from that professional role.
-
D.
notableTheorist
chosen
Indicates that the subject is recognized as a significant or influential theorist in relation to the object or specified field.
-
E.
eponymDiscoveredFor
Indicates that something is named after a person who discovered or first identified it.
- 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:11 p.m.