Triple
T17173677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Project Juno |
E416801
|
entity |
| Predicate | notableParticipantOccupation |
P6467
|
FINISHED |
| Object | chemist |
—
|
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: chemist | Statement: [Project Juno, notableParticipantOccupation, chemist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableParticipantOccupation Context triple: [Project Juno, notableParticipantOccupation, chemist]
-
A.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
-
B.
notableParticipant
chosen
Indicates that an entity plays a significant or distinguished role as a participant in an event, activity, or context.
-
C.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
D.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
E.
notableCharacterOccupation
Indicates that a notable character is associated with a specific occupation or professional 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0b7c9c819082e503cb493d7e7b |
completed | April 18, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.