Triple
T8026165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | August Borsig |
E186858
|
entity |
| Predicate | industryOfWork |
P62124
|
FINISHED |
| Object | rail transport industry |
—
|
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: rail transport industry | Statement: [August Borsig, industryOfWork, rail transport industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industryOfWork Context triple: [August Borsig, industryOfWork, rail transport industry]
-
A.
industryStart
Indicates the point in time or event at which an industry, industrial activity, or industrial era begins.
-
B.
industryContext
Indicates the industry or sector within which an entity, activity, or relationship is situated or most relevant.
-
C.
industryConnection
Indicates a professional or business relationship linking entities within the same or related industries, such as partnerships, collaborations, or shared sector involvement.
-
D.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
-
E.
professionalSector
chosen
Indicates the industry or field in which an entity conducts its professional or occupational activities.
- F. None of above.
Provenance (3 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_69ca82ad4e2c8190a693e3c9e30fe66f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ecb00648190bb3144acf3492bb3 |
completed | March 31, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69cb049253d08190bafcecfde493ab8b |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:21 p.m.