Triple
T4182620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Arginusae |
E88227
|
entity |
| Predicate | fleetSize (Athens) |
P1848
|
FINISHED |
| Object | about 150 triremes |
—
|
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: about 150 triremes | Statement: [Battle of Arginusae, fleetSize (Athens), about 150 triremes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fleetSize (Athens) Context triple: [Battle of Arginusae, fleetSize (Athens), about 150 triremes]
-
A.
fleetSize
chosen
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
B.
navalFleet
Indicates a relationship where multiple naval vessels are organized and operate together as a coordinated maritime military force.
-
C.
fleetName
Indicates the name assigned to a particular fleet within a system or context.
-
D.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
E.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:45 p.m.