Triple
T37239535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian National Research Council |
E923673
|
entity |
| Predicate | numberOfResearchers |
P113084
|
FINISHED |
| Object | several thousand |
—
|
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: several thousand | Statement: [Italian National Research Council, numberOfResearchers, several thousand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfResearchers Context triple: [Italian National Research Council, numberOfResearchers, several thousand]
-
A.
numberOfScientists
chosen
Indicates the quantity of scientists associated with a given entity or context.
-
B.
academicStaffCountApprox
Indicates an approximate number of academic staff associated with an institution or organizational unit.
-
C.
numberOfPapers
Indicates the quantity of papers associated with a given entity.
-
D.
numberOfResearchCentres
Indicates the quantity of research centres associated with a given entity.
-
E.
researchUser
Indicates that an entity conducts research on, studies, or investigates a particular user.
- 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_69f76ea9fee88190a589f661d95a7189 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.