Triple
T24964050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lassell (Triton) |
E624688
|
entity |
| Predicate | eponymDiscoveredObject |
P117775
|
FINISHED |
| Object | Triton |
—
|
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: Triton | Statement: [Lassell (Triton), eponymDiscoveredObject, Triton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eponymDiscoveredObject Context triple: [Lassell (Triton), eponymDiscoveredObject, Triton]
-
A.
eponymOfDiscovererOf
Indicates that one entity gives its name to the person who discovered another 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.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
D.
eponymProfession
Indicates that a person’s profession is the source of an eponym, i.e., a word or name derived from that professional role.
-
E.
subjectOfDiscovery
chosen
Indicates that an entity is the topic, object, or focus that has been discovered in a discovery event or process.
- 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_69e2ff23a3a88190b1b9743fe5e15f94 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f4490283c481908c18246dc7125eec |
completed | May 1, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 5:59 a.m.