Triple
T810396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burma Road |
E17529
|
entity |
| Predicate | closureYear |
P19867
|
FINISHED |
| Object | 1942 |
—
|
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: 1942 | Statement: [Burma Road, closureYear, 1942]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closureYear Context triple: [Burma Road, closureYear, 1942]
-
A.
closureReason
Indicates the reason or cause for which an entity, process, or case has been closed or terminated.
-
B.
closureProcess
Indicates the procedure or set of actions carried out to formally conclude, finalize, or terminate an ongoing activity, case, or process.
-
C.
closedDuring
Indicates that an entity is not open or available for use during a specified time period or under certain conditions.
-
D.
closedIn
Indicates that one entity is enclosed, contained, or surrounded within the boundaries or limits defined by another entity.
-
E.
closedUnder
Indicates that applying a specified operation to elements within a set always produces a result that is also an element of that same set.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab4c7418819085cb64c6bf5fa70c |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa73df08819096d0553a4b2509de |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4781c88190ae36906251347cdc |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:38 p.m.