Triple
T17091809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Defense Manpower Data Center |
E414743
|
entity |
| Predicate | managesSystem |
P76502
|
FINISHED |
| Object | DEERS |
E414744
|
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: DEERS | Statement: [Defense Manpower Data Center, managesSystem, DEERS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DEERS Context triple: [Defense Manpower Data Center, managesSystem, DEERS]
-
A.
DEERS
chosen
DEERS is a U.S. Department of Defense database that manages and verifies service members’ and their dependents’ eligibility for military benefits and healthcare.
-
B.
Ezo deer
The Ezo deer is a subspecies of sika deer native to Japan’s northern island of Hokkaido, known for its large size and adaptation to cold, snowy environments.
-
C.
Deerlijk
Deerlijk is a municipality in the Belgian province of West Flanders.
-
D.
The Deer
The Deer is a character in the animated film "The Voices," portrayed through both acting and voice work by the same lead performer.
-
E.
tufted deer
The tufted deer is a small, shy East Asian deer species known for its distinctive black forehead tuft and short, fang-like upper canines.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbfa09b08190be4303dd0d174feb |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012eec0d5c8190806e756aae848ba2 |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:35 a.m.