Triple
T3750741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Kembla |
E81321
|
entity |
| Predicate | majorImport |
P51103
|
FINISHED |
| Object | motor vehicles |
—
|
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: motor vehicles | Statement: [Port Kembla, majorImport, motor vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorImport Context triple: [Port Kembla, majorImport, motor vehicles]
-
A.
majorImpact
Indicates that one entity has a significant, highly influential, or transformative effect on another entity or outcome.
-
B.
majorExport
Indicates that something is a primary or significant export product or resource of a given entity (such as a country or region).
-
C.
majorUse
Indicates that something serves as the primary or most significant use or application of an entity.
-
D.
majorIssue
Indicates that something is a primary or most significant problem, concern, or obstacle in a given context.
-
E.
majorStatus
Indicates that an entity holds primary or most significant status relative to others in a given context.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb909bb4819088559f90d718f72f |
completed | March 8, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69adc04adebc819088d7f36d0ac343a6 |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc1560c248190b07438d766880990 |
completed | March 8, 2026, 6:35 p.m. |
Created at: March 8, 2026, 3:35 p.m.