Triple
T754949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie Curie |
E15532
|
entity |
| Predicate | NobelPrizeInChemistryYear |
P1862
|
FINISHED |
| Object | 1911 |
—
|
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: 1911 | Statement: [Marie Curie, NobelPrizeInChemistryYear, 1911]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NobelPrizeInChemistryYear Context triple: [Marie Curie, NobelPrizeInChemistryYear, 1911]
-
A.
NobelPrizeYear
chosen
Indicates the specific year in which an entity received or was awarded a Nobel Prize.
-
B.
ageAtNobelPrize
Indicates the age a person was when they received a Nobel Prize.
-
C.
NobelPrizeCategory
Indicates the specific Nobel Prize field or discipline (such as Physics, Literature, or Peace) associated with an award or laureate.
-
D.
roleInNobelPrize
Indicates the specific capacity or function an entity had in relation to a particular Nobel Prize (e.g., laureate, nominee, organization, or associated role).
-
E.
nobelPrizeRelated
Indicates that there is a connection or association between an entity and the Nobel Prize, such as receiving, being nominated for, or otherwise being significantly linked to 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.