Triple
T12748724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Grand Old Lady |
E304675
|
entity |
| Predicate | refersToShipType |
P89044
|
FINISHED |
| Object | dreadnought battleship |
—
|
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: dreadnought battleship | Statement: [The Grand Old Lady, refersToShipType, dreadnought battleship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToShipType Context triple: [The Grand Old Lady, refersToShipType, dreadnought battleship]
-
A.
appliesToShips
Indicates that the specified condition, rule, or attribute is relevant to or affects ships.
-
B.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
C.
laterShipType
Indicates that one ship type chronologically succeeds or is introduced after another ship type.
-
D.
hasShipCategory
chosen
Indicates that an entity is associated with or classified under a particular category or type of ship.
-
E.
shipsWith
Indicates that one entity is delivered, packaged, or provided together with another entity as part of the same shipment or bundle.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.