Triple
T251608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office of Defense Health and Welfare Services |
E5159
|
entity |
| Predicate | isFocusedOn |
P31
|
FINISHED |
| Object | civilian health |
—
|
LITERAL 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: civilian health | Statement: [Office of Defense Health and Welfare Services, isFocusedOn, civilian health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFocusedOn Context triple: [Office of Defense Health and Welfare Services, isFocusedOn, civilian health]
-
A.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
isOn
Indicates that one entity is physically positioned above and in contact with the top surface of another entity.
-
C.
mayProvideFocus
Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
-
D.
isAt
Indicates that one entity is located at or present in the place or position of another entity.
-
E.
endsOn
Indicates that one entity terminates or concludes precisely at the boundary or endpoint of another entity.
- F. None of above.
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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d38aba8819081d0958eb60ce27e |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b678d6c81909780e1995c1ca691 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.