Triple
T17011629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M100 series trains |
E412713
|
entity |
| Predicate | refurbished |
P86076
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [M100 series trains, refurbished, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refurbished Context triple: [M100 series trains, refurbished, yes]
-
A.
refurbishedIn
chosen
Indicates that an entity has undergone restoration, repair, or renovation at a specific time or during a particular period.
-
B.
repairedIn
Indicates that an item or object underwent repair within a specified location or during a particular time period.
-
C.
refurbishedForMuseumUse
Indicates that something has been restored or modified specifically to be suitable for display or use in a museum context.
-
D.
rebuiltFor
Indicates that one entity has been reconstructed, renovated, or modified specifically to serve the needs, purposes, or use of another entity.
-
E.
recommissioned
Indicates that something previously deactivated, retired, or out of service has been restored and formally returned to active use or operation.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d47cc17c819087f7bd27582bcbfa |
completed | April 18, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.