Triple
T8197409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birmingham Moor Street railway station |
E191466
|
entity |
| Predicate | hasRebuilding |
P28319
|
FINISHED |
| Object | restoration in early 2000s |
—
|
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: restoration in early 2000s | Statement: [Birmingham Moor Street railway station, hasRebuilding, restoration in early 2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRebuilding Context triple: [Birmingham Moor Street railway station, hasRebuilding, restoration in early 2000s]
-
A.
hasRebuilt
Indicates that an entity has restored, reconstructed, or built again something that previously existed or was damaged or destroyed.
-
B.
hasRebuiltDate
Indicates the date on which something was rebuilt or reconstructed.
-
C.
hasReconstructionWork
chosen
Indicates that an entity is undergoing, has undergone, or is associated with reconstruction or restoration work.
-
D.
notRebuiltAfter
Indicates that an entity was destroyed or damaged and has not been reconstructed or restored after a specified event or point in time.
-
E.
haveReconstructionWork
Indicates that an entity is undergoing or is associated with reconstruction or restoration work.
- 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_69ca82c6e9548190a4c5ca14516e4417 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5c2341f881908be59c378896e5bc |
completed | March 31, 2026, 5:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36aac86081909b83636e352e0ced |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:42 p.m.