Triple
T146056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lifelong Learning Machines program |
E3332
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object |
L2M
L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
|
E17403
|
NE FINISHED |
How this triple was built (4 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: L2M | Statement: [Lifelong Learning Machines program, acronym, L2M]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: L2M Context triple: [Lifelong Learning Machines program, acronym, L2M]
-
A.
LCC
LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
-
B.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
C.
L.A.M.C.
L.A.M.C. is the commonly used abbreviation for the Los Angeles Municipal Code, the body of local laws and regulations governing the City of Los Angeles.
-
D.
LBY
LBY is the three-letter ISO 3166-1 alpha-3 country code assigned to Libya.
-
E.
MC
MC is the official abbreviation for NATO’s highest military authority, the NATO Military Committee.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: L2M Triple: [Lifelong Learning Machines program, acronym, L2M]
Generated description
L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: L2M Target entity description: L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
-
A.
LCC
LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
-
B.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
C.
L.A.M.C.
L.A.M.C. is the commonly used abbreviation for the Los Angeles Municipal Code, the body of local laws and regulations governing the City of Los Angeles.
-
D.
LBY
LBY is the three-letter ISO 3166-1 alpha-3 country code assigned to Libya.
-
E.
MC
MC is the official abbreviation for NATO’s highest military authority, the NATO Military Committee.
- F. None of above. chosen
Provenance (5 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257ea7eac8190884a53453a9e0dd6 |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c2763ce481908c12046de9003a84 |
completed | Feb. 28, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69a2c2f02810819092e3263ac91b5fe3 |
completed | Feb. 28, 2026, 10:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2c369498481908c4213b04aea9c97 |
completed | Feb. 28, 2026, 10:28 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.