Triple
T5502006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Train Operating Companies |
E144349
|
entity |
| Predicate | mayLease |
P46530
|
FINISHED |
| Object | rolling stock from rolling stock companies |
—
|
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: rolling stock from rolling stock companies | Statement: [Train Operating Companies, mayLease, rolling stock from rolling stock companies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayLease Context triple: [Train Operating Companies, mayLease, rolling stock from rolling stock companies]
-
A.
mayHold
Indicates that one entity is permitted or allowed to possess, contain, or maintain another entity.
-
B.
mayEnter
Indicates that one entity is permitted or authorized to enter or access another entity or location.
-
C.
wasLeasedFor
Indicates that one entity was leased in exchange for a specified payment amount, purpose, or consideration.
-
D.
mayHost
Indicates that an entity is permitted or able to serve as the location or organizer for another entity or event.
-
E.
leaseContext
chosen
Indicates the contextual circumstances, terms, or conditions under which a lease agreement or leasing relationship exists or is interpreted.
- 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_69c008f5a2748190bce7a39aabf87a6d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f0a512c81908f077378917e5879 |
completed | March 22, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69c01b052f3c81909f71c6add0f35a6f |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:32 p.m.