Triple
T32027358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SC |
E817853
|
entity |
| Predicate | hasRoleArea |
P194430
|
FINISHED |
| Object | logistics |
—
|
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: logistics | Statement: [SC, hasRoleArea, logistics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoleArea Context triple: [SC, hasRoleArea, logistics]
-
A.
hasRole
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
B.
hasSecurityArea
Indicates that an entity is associated with, assigned to, or falls within a defined security-controlled area or zone.
-
C.
hasLegalRole
Indicates that an entity holds a specific legal capacity, status, or function in relation to another entity or context.
-
D.
hasQuadrantRole
Indicates that an entity holds a specific functional or positional role within a defined quadrant of a larger structure or system.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69f348fb04e4819081f4eab040ed7959 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
| PDg | Predicate description generation | batch_69fd6f9a8bd881909983fe8f4cd0ba98 |
completed | May 8, 2026, 5:07 a.m. |
Created at: May 1, 2026, 12:17 a.m.