Triple
T32765201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Farragut (DDG-99) |
E837874
|
entity |
| Predicate | namedAfterCountryService |
P182781
|
FINISHED |
| Object | United States Navy admiral |
—
|
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: United States Navy admiral | Statement: [USS Farragut (DDG-99), namedAfterCountryService, United States Navy admiral]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterCountryService Context triple: [USS Farragut (DDG-99), namedAfterCountryService, United States Navy admiral]
-
A.
namedAfterCountryAssociation
Indicates that one entity is named after, or derives its name from, a specific country.
-
B.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
C.
namedAfterCountryOfOrigin
Indicates that an entity is named after the country from which it originates or was first produced.
-
D.
countryAfterIntegration
Indicates the country that exists as a result of, or following, an integration or unification process involving another entity.
-
E.
designationCountry
Indicates the country that officially assigns or confers a particular status, title, or designation on an entity.
- 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_69f34939857c8190aa9970c51feec1eb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7908ec35881909a42f954fb9fa16e |
completed | May 3, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78fd3fd888190b7db0b563f298585 |
completed | May 3, 2026, 6:11 p.m. |
Created at: May 1, 2026, 1:13 a.m.