Triple
T6327258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-Code |
E141890
|
entity |
| Predicate | hasUserSegment |
P70062
|
FINISHED |
| Object | military GPS receivers |
—
|
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: military GPS receivers | Statement: [M-Code, hasUserSegment, military GPS receivers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUserSegment Context triple: [M-Code, hasUserSegment, military GPS receivers]
-
A.
hasUser
Indicates that an entity is associated with or linked to a specific user.
-
B.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
C.
hasUserGroup
Indicates that a user is associated with, belongs to, or is a member of a specific user group.
-
D.
hasUserService
Indicates that an entity is associated with or utilizes a particular user-related service.
-
E.
hasExpressSegments
Indicates that a route, service, or path includes segments that are designated as express, skipping certain intermediate stops or steps.
- 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064e9532081908277f10ec380a486 |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e5efc48190861b8266e5b0cc0c |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:29 p.m.