Triple
T35523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secretary of the Army |
E702
|
entity |
| Predicate | includedIn |
P1393
|
FINISHED |
| Object | line of succession to the Secretary of Defense |
—
|
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: line of succession to the Secretary of Defense | Statement: [Secretary of the Army, includedIn, line of succession to the Secretary of Defense]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedIn Context triple: [Secretary of the Army, includedIn, line of succession to the Secretary of Defense]
-
A.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
B.
featuredIn
Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
-
C.
annexedBy
Indicates that one entity has been incorporated into and brought under the control or sovereignty of another entity.
-
D.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
E.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24989c3308190af59dfae37cfc32f |
completed | Feb. 28, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69a24873e97c8190b9e4279e43b6de14 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.