Triple
T15070348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Versailles arms limitations |
E379858
|
entity |
| Predicate | limitedBattleshipsTo |
P39920
|
FINISHED |
| Object | 6 pre-dreadnought battleships |
—
|
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: 6 pre-dreadnought battleships | Statement: [Versailles arms limitations, limitedBattleshipsTo, 6 pre-dreadnought battleships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: limitedBattleshipsTo Context triple: [Versailles arms limitations, limitedBattleshipsTo, 6 pre-dreadnought battleships]
-
A.
battleshipInvolved
Indicates that a battleship participates as an active party in a specific event, operation, or engagement.
-
B.
numberOfBattleshipsCompleted
Indicates the total count of battleships that have been fully constructed or completed.
-
C.
numberOfShips
chosen
Indicates the quantity of ships associated with a given entity or situation.
-
D.
battleshipsDamaged
Indicates that one or more battleships have sustained damage, typically as a result of combat or hostile action.
-
E.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7f86df48190b3a2cf441fefb477 |
completed | April 15, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:02 a.m.