Triple
T7001612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swiss flag |
E162349
|
entity |
| Predicate | proportionOnShips |
P73518
|
FINISHED |
| Object | 2:3 |
—
|
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: 2:3 | Statement: [Swiss flag, proportionOnShips, 2:3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proportionOnShips Context triple: [Swiss flag, proportionOnShips, 2:3]
-
A.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
B.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
C.
otherShipsInFleet
Indicates that the subject ship and the object ship are distinct members of the same fleet.
-
D.
componentShip
Indicates that one entity is a physical or logical component or part of another entity, such that the whole is composed of or depends on that component.
-
E.
classShipCount
Indicates the number of ships associated with a particular class or category.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc0f8830819091f4356296234713 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c575f081908b43d95d1d99b1a4 |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:33 p.m.