Triple
T3100872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal School of Signals |
E64713
|
entity |
| Predicate | hasMotto |
P42
|
FINISHED |
| Object | Certa Cito |
E326647
|
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: Certa Cito | Statement: [Royal School of Signals, hasMotto, Certa Cito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Certa Cito Context triple: [Royal School of Signals, hasMotto, Certa Cito]
-
A.
Certa Cito
chosen
Certa Cito is the Latin motto of the British Army’s Royal Corps of Signals, reflecting their role in providing swift and reliable military communications.
-
B.
Citura
Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
-
C.
Biqueli
Biqueli is a small coastal settlement on Atauro Island in East Timor, known for its fishing community and proximity to coral reefs.
-
D.
Niva
Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
-
E.
Fiat Uno
The Fiat Uno is a compact city car produced by the Italian manufacturer Fiat, known for its practicality, fuel efficiency, and popularity in European and Latin American markets since the 1980s.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada26b03a081909cf187b9a8f805ce |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f563524819084ae75c024b8291d |
completed | March 12, 2026, 12:56 a.m. |
Created at: March 8, 2026, 3:03 p.m.