Triple
T33362278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green fluorescent protein |
E854252
|
entity |
| Predicate | wasCoAwardedNobelPrizeIn |
P69892
|
FINISHED |
| Object | Chemistry 2008 |
—
|
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: Chemistry 2008 | Statement: [Green fluorescent protein, wasCoAwardedNobelPrizeIn, Chemistry 2008]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasCoAwardedNobelPrizeIn Context triple: [Green fluorescent protein, wasCoAwardedNobelPrizeIn, Chemistry 2008]
-
A.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
-
B.
NobelPrizeCategory
Indicates the specific Nobel Prize field or discipline (such as Physics, Literature, or Peace) associated with an award or laureate.
-
C.
namedForNobelLaureate
Indicates that one entity bears a name derived from or in honor of a Nobel Prize laureate.
-
D.
NobelPrizeCoLaureate
chosen
Indicates that two or more individuals share the same Nobel Prize as co-recipients for a particular award and year.
-
E.
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).
- 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_69f3496bda8c8190bfc8fade9d1b791c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f38159d08190980ad639e08f00f4 |
completed | May 3, 2026, 7:04 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d7bee48190b94e0beb48a1d7fa |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:34 a.m.