Triple
T227616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Field Artillery Branch |
E4344
|
entity |
| Predicate | hasEnlistedCareerManagementField |
P9319
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Field Artillery Branch, hasEnlistedCareerManagementField, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnlistedCareerManagementField Context triple: [Field Artillery Branch, hasEnlistedCareerManagementField, 13]
-
A.
isStageInCareerOf
Indicates that one entity represents a particular phase or stage within the professional career of another entity.
-
B.
hasWorkInCollection
Indicates that a work or item is included as part of a particular collection.
-
C.
hasMemberState
Indicates that an entity includes or comprises another entity as one of its constituent member states within a larger organizational or political structure.
-
D.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
-
E.
describesCareerOf
Indicates that one entity provides a description or characterization of the professional career of another entity.
- F. None of above. chosen
Provenance (4 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d10ac248190a98dedabf5358668 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b5877588190af694d060377f027 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25d0ec71081908478c800be4f7bb0 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.