Triple
T14604698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamerlingh Onnes |
E342797
|
entity |
| Predicate | eponymKnownFor |
P115018
|
FINISHED |
| Object | low-temperature physics |
—
|
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: low-temperature physics | Statement: [Kamerlingh Onnes, eponymKnownFor, low-temperature physics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eponymKnownFor Context triple: [Kamerlingh Onnes, eponymKnownFor, low-temperature physics]
-
A.
eponymPlayedFor
Indicates that the eponymous person or entity was a member of, or played for, a particular team or organization.
-
B.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
C.
eponymousFounderOf
Indicates that a person is the namesake founder after whom an organization, place, or entity is named.
-
D.
eponymCountry
Indicates that a country is named after (or serves as the namesake for) a particular person, place, or entity.
-
E.
hasEponymConnectionTo
Indicates that one entity is named after, derived from, or otherwise linguistically or honorifically connected to another entity as its eponym.
- F. None of above. chosen
Provenance (4 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb44bf67c8190b4c48a7715f9443e |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:25 a.m.