Triple
T24569986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | convoy JW 55B |
E607907
|
entity |
| Predicate | numberOfEscortVessels |
P39920
|
FINISHED |
| Object | over 20 |
—
|
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: over 20 | Statement: [convoy JW 55B, numberOfEscortVessels, over 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEscortVessels Context triple: [convoy JW 55B, numberOfEscortVessels, over 20]
-
A.
typeOfVesselEscorted
Indicates the specific kind of vessel that is being accompanied or protected in an escorting relationship.
-
B.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
C.
numberOfShips
chosen
Indicates the quantity of ships associated with a given entity or situation.
-
D.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
-
E.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
- 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_69e2c4cc35a48190990b7571bc086df8 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a923635c819097ecac0c82ec5f29 |
completed | April 30, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:28 a.m.