Triple
T36333823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Range Navigation |
E894724
|
entity |
| Predicate | countryWithExtendedUse |
P198244
|
FINISHED |
| Object | United States |
E14
|
NE 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 | Statement: [Long Range Navigation, countryWithExtendedUse, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryWithExtendedUse Context triple: [Long Range Navigation, countryWithExtendedUse, United States]
-
A.
secondaryCountryOfUse
chosen
Indicates that an entity is used or applied in a country that is not its primary country of use but serves as an additional or secondary location of use.
-
B.
usedWithCountryName
Indicates that something (such as a term, label, or identifier) is used specifically in conjunction with a country name.
-
C.
countryOfSymbolicUse
Indicates the country in which something (such as a symbol, object, or element) is used in a symbolic or representative way.
-
D.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
-
E.
usedForCountry
Indicates that something is used for, or serves a purpose related to, a specific country.
- F. None of above.
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_69f76e4e90148190b02fe52593c70b5b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0301289dbc8190a4372958d3451171 |
completed | May 12, 2026, 10:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a39c3f31fe08190a3317e7b923d842b |
completed | June 22, 2026, 11:23 p.m. |
| PD | Predicate disambiguation | batch_6a0300d4185c8190a383d5da3659bc4f |
completed | May 12, 2026, 10:28 a.m. |
Created at: May 3, 2026, 4:09 p.m.