Triple
T66259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SecDef |
E1320
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | SecDef |
E1320
|
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: SecDef | Statement: [SecDef, shortForm, SecDef]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SecDef Context triple: [SecDef, shortForm, SecDef]
-
A.
SecDef
chosen
SecDef is the commonly used abbreviation for the United States Secretary of Defense, the head of the Department of Defense and principal defense policy advisor to the U.S. President.
-
B.
GM Defense
GM Defense is a General Motors division that designs and manufactures advanced military and defense mobility solutions, including tactical vehicles and autonomous platforms, for government and defense customers.
-
C.
This We'll Defend
"This We'll Defend" is the historic motto of the United States Army, expressing its mission to protect and defend the nation and its people.
-
D.
SCC
SCC is the commonly used abbreviation for the MIT Schwarzman College of Computing, an interdisciplinary hub for computing and AI research and education.
-
E.
SIG
SIG is an acronym commonly used by the Association for Computing Machinery to denote its specialized Special Interest Groups that focus on particular areas of computing research and practice.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a24f01a2108190a494e7bfcced8290 |
completed | Feb. 28, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2554da8848190a445b503d98769aa |
completed | Feb. 28, 2026, 2:39 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.