Triple
T5709835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida-class battleship |
E125877
|
entity |
| Predicate | hasShipNumberRange |
P65724
|
FINISHED |
| Object | BB-30 to BB-31 |
—
|
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: BB-30 to BB-31 | Statement: [Florida-class battleship, hasShipNumberRange, BB-30 to BB-31]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShipNumberRange Context triple: [Florida-class battleship, hasShipNumberRange, BB-30 to BB-31]
-
A.
articleNumberRange
Indicates that something is associated with or falls within a specified range of article numbers.
-
B.
hasShipPrefix
Indicates that a ship is associated with or identified by a specific prefix in its name or designation.
-
C.
hasShipLock
Indicates that one entity possesses or is equipped with a ship lock used to control water levels for vessel passage.
-
D.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
E.
hasShip
Indicates that one entity possesses, owns, or is equipped with a ship.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0248c3dac8190824fca9ddde89665 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c023dfec6881909ee6189b874b4348 |
completed | March 22, 2026, 5:16 p.m. |
Created at: March 22, 2026, 3:46 p.m.