Triple
T8554066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NS Sprinter |
E202518
|
entity |
| Predicate | safetySystem |
P840
|
FINISHED |
| Object | ATB-EG |
E153680
|
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: ATB-EG | Statement: [NS Sprinter, safetySystem, ATB-EG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ATB-EG Context triple: [NS Sprinter, safetySystem, ATB-EG]
-
A.
ATB-EG
chosen
ATB-EG is a Dutch train protection and signalling system used to control train speeds and enhance safety on the national railway network.
-
B.
ABT
ABT is the stock ticker symbol for Abbott Laboratories, a global healthcare company specializing in medical devices, diagnostics, nutrition products, and branded generic pharmaceuticals.
-
C.
ABT
ABT is a leading American classical ballet company renowned for its extensive repertoire and international tours.
-
D.
ATN
ATN most likely refers to Augmented Transition Network, a type of finite state machine used in computational linguistics and natural language processing for parsing sentences.
-
E.
ATZ
ATZ is the IATA airport code for Assiut Airport, a regional airport serving the city of Assiut in Egypt.
- 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe8894e7c8190bc0ae2ceec473ecb |
completed | March 31, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6dd67d288190a147562a99ecde56 |
completed | April 2, 2026, 1:23 p.m. |
Created at: March 30, 2026, 6:19 p.m.