Triple
T30377745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle between USS Constitution and HMS Cyane and HMS Levant |
E772736
|
entity |
| Predicate | countryOfOriginOfUSSConstitution |
P26
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Battle between USS Constitution and HMS Cyane and HMS Levant, countryOfOriginOfUSSConstitution, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfOriginOfUSSConstitution Context triple: [Battle between USS Constitution and HMS Cyane and HMS Levant, countryOfOriginOfUSSConstitution, United States]
-
A.
countryOfBritishShips
Indicates the country to which British ships belong or are registered.
-
B.
historicalOriginCountry
Indicates the country from which something originally came or first emerged in a historical context.
-
C.
countryOfShipSunk
Indicates the country to which a ship that was sunk belonged or was registered.
-
D.
countryOfOrigin
chosen
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
E.
nationalityOfVessels
Indicates the country or flag state to which vessels legally belong or are registered.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff6ef0d61c81909162d37c15a1a3c3 |
completed | May 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ff6c6a58e08190921317062cd9d489 |
completed | May 9, 2026, 5:18 p.m. |
Created at: April 29, 2026, 8 p.m.