Triple
T24491706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Via Panisperna |
E617656
|
entity |
| Predicate | hasAssociatedResearchGroup |
P156520
|
FINISHED |
| Object | Via Panisperna boys |
—
|
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: Via Panisperna boys | Statement: [Via Panisperna, hasAssociatedResearchGroup, Via Panisperna boys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedResearchGroup Context triple: [Via Panisperna, hasAssociatedResearchGroup, Via Panisperna boys]
-
A.
hasAcademicFieldGroup
Indicates that an entity is associated with, or belongs to, a particular group or category of academic fields.
-
B.
hasResearchGroupWebsite
Indicates that a research group is associated with or maintains a specific website.
-
C.
hasResearcher
Indicates that an entity is associated with or linked to a specific researcher responsible for work, study, or investigation related to it.
-
D.
hasAcademicAssociation
Indicates a relationship where one entity is connected to another through an academic context, such as study, research, teaching, or institutional affiliation.
-
E.
hasResearchComponent
Indicates that an entity includes, involves, or is associated with a research-related component or activity.
- 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_69e2d7f4e6bc8190aec540ae3b9ed7f2 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a9d795288190916368e3cec1f666 |
completed | April 30, 2026, 1:01 a.m. |
Created at: April 18, 2026, 2:22 a.m.