Triple
T18874488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Working Party on Passive Safety |
E461648
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | GRSP |
—
|
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: GRSP | Statement: [Working Party on Passive Safety, shortName, GRSP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GRSP Context triple: [Working Party on Passive Safety, shortName, GRSP]
-
A.
GRSP
chosen
GRSP is an international alliance of governments, businesses, and civil society organizations dedicated to improving road safety and reducing traffic-related deaths and injuries worldwide.
-
B.
GRA
GRA is the ring-shaped orbital motorway encircling Rome, Italy, serving as a major traffic artery for the metropolitan area.
-
C.
KGSP
KGSP is the ICAO airport code for Greenville–Spartanburg International Airport, a major commercial airport serving the Upstate region of South Carolina, USA.
-
D.
GRNP
GRNP is a South African national park along the Garden Route famed for its indigenous forests, dramatic coastline, and rich biodiversity.
-
E.
GRPM
GRPM is a regional museum in Grand Rapids, Michigan, known for its exhibits on local history, science, and culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3cd49748190948d535918aec3de |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 10, 2026, 11:57 a.m.