Triple
T15924739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Anti-Terrorist Unit of Serbia |
E386178
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | SAJ |
E893562
|
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: SAJ | Statement: [Special Anti-Terrorist Unit of Serbia, hasAbbreviation, SAJ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SAJ Context triple: [Special Anti-Terrorist Unit of Serbia, hasAbbreviation, SAJ]
-
A.
SAJ
SAJ is the National Rail station code for St Johns railway station in southeast London, England.
-
B.
SAJ
SAJ is a Jewish congregation and community in New York City historically associated with the Reconstructionist movement and progressive Jewish practice.
-
C.
SAJ
chosen
SAJ is the Ski Association of Japan, the national governing body for ski sports in Japan, including ski jumping.
-
D.
SA3
SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
-
E.
SAIT
SAIT is a Canadian polytechnic institute in Calgary, Alberta, offering career-focused technical, trades, and applied degree programs.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1568424f08190bffe6ee465a0db9a |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5adcde88190ae2a845aaa9d31ac |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:52 a.m.