Triple
T21956421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Contractor |
E542198
|
entity |
| Predicate | hasMilitaryTheme |
P146691
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Contractor, hasMilitaryTheme, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryTheme Context triple: [The Contractor, hasMilitaryTheme, true]
-
A.
militarySupportTheme
Indicates that one entity provides, requests, or is associated with military assistance, backing, or involvement in relation to another entity or situation.
-
B.
hasMilitarySignificance
Indicates that something holds strategic or tactical importance for military planning, operations, or defense objectives.
-
C.
hasMilitaryType
Indicates that an entity is associated with or classified under a specific military category, role, or type.
-
D.
hasMilitarySecurity
Indicates that an entity provides, maintains, or is responsible for military protection or defense for another entity or area.
-
E.
hasMilitaryAssociation
Indicates a relationship in which an entity is connected or affiliated with a military organization, activity, or function.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124404f38819080bae736a52a51cd |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb9b75308190addc3dba7b5d5ddd |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:59 p.m.