Triple
T14693752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Astute programme |
E345100
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | SSN |
E803732
|
NE 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: SSN | Statement: [Astute programme, abbreviation, SSN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SSN Context triple: [Astute programme, abbreviation, SSN]
-
A.
SSN
chosen
SSN is the NATO reporting name used to designate nuclear-powered attack submarines, such as those of the Victor class.
-
B.
SSN
SSN is the abbreviation for Mexico’s National Seismological Service, the official agency responsible for monitoring and reporting seismic activity in the country.
-
C.
Social Security number
A Social Security number is a unique nine-digit identifier issued to U.S. residents primarily for tracking earnings and determining eligibility for government benefits, and widely used for identification in financial and legal contexts.
-
D.
SSA
SSA is a professional scientific organization dedicated to advancing the study and understanding of earthquakes and seismic phenomena.
-
E.
SSA
SSA is the IATA airport code for Deputado Luís Eduardo Magalhães International Airport serving Salvador, Brazil.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb586e7108190be644db9cf9a4d99 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde18e279c8190814f90e947734541 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:28 a.m.