Triple
T36251556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Yorktown |
E891815
|
entity |
| Predicate | repairedInTimeFor |
P185064
|
FINISHED |
| Object | Battle of Midway |
—
|
NE NERFINISHED |
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: Battle of Midway | Statement: [USS Yorktown, repairedInTimeFor, Battle of Midway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: repairedInTimeFor Context triple: [USS Yorktown, repairedInTimeFor, Battle of Midway]
-
A.
repairedIn
Indicates that an item or object underwent repair within a specified location or during a particular time period.
-
B.
isRepairable
Indicates that an entity can be restored to proper working condition through repair.
-
C.
repairsCompleted
Indicates that a previously initiated repair action or process has been fully carried out and successfully finished.
-
D.
rebuiltCompletedIn
Indicates that an entity has undergone a rebuilding process that was fully completed in a specified time or event.
-
E.
recoveredIn
Indicates that something lost, damaged, or impaired has been restored or regained within a particular context, process, or location.
- 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_69f76e4599108190811532e707d6bc2c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.