Triple
T3086062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamato-class battleship |
E64375
|
entity |
| Predicate | numberOfBattleshipsCompleted |
P45789
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Yamato-class battleship, numberOfBattleshipsCompleted, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBattleshipsCompleted Context triple: [Yamato-class battleship, numberOfBattleshipsCompleted, 2]
-
A.
voyagesCompleted
Indicates that an entity has successfully finished one or more journeys or trips from departure to return.
-
B.
numberLaunchedInCombat
Indicates the quantity of times an entity has been launched or deployed specifically in combat operations.
-
C.
receivedBattleStars
Indicates that an entity has been awarded one or more battle stars for participation in specific military engagements or campaigns.
-
D.
numberOfMissions
Indicates the total count of missions associated with a given entity or context.
-
E.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
- 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_69ad857bb4c88190a4cf27893fcabed8 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1eac5548190bee60ea8262c65a8 |
completed | March 8, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69ad9ded78f881908be6fc0fb7c35764 |
completed | March 8, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:03 p.m.