Triple
T2384283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CADE Inc. |
E46381
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | CADE |
E260061
|
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: CADE | Statement: [CADE Inc., abbreviation, CADE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CADE Context triple: [CADE Inc., abbreviation, CADE]
-
A.
CADE
chosen
CADE is a leading international conference focused on research and advances in automated reasoning and automated theorem proving.
-
B.
CCA
CCA is the ICAO airline designator used to identify Air China in international aviation operations.
-
C.
CAC
The Central American Cup (CAC) is a regional football tournament featuring national teams from Central America competing for the championship title.
-
D.
CAC
CAC is the commonly used abbreviation for the U.S. Army Combined Arms Center, a key institution responsible for developing Army doctrine, training, and leader education.
-
E.
CAF
CAF is a Spanish multinational company that designs and manufactures railway vehicles and related transport equipment used by metro systems worldwide.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7bc87d0819090cd9d19d748bcc3 |
completed | March 7, 2026, 6:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef094fd8081909fc9a19f3e36c0d0 |
completed | March 9, 2026, 4:08 p.m. |
Created at: March 4, 2026, 7:57 p.m.