Triple
T4429539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marine Forces South |
E95289
|
entity |
| Predicate | commonPartnerLanguages |
P741
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Marine Forces South, commonPartnerLanguages, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonPartnerLanguages Context triple: [Marine Forces South, commonPartnerLanguages, Spanish]
-
A.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
B.
languagesSpoken
chosen
Indicates that an entity is able to communicate using one or more specified languages.
-
C.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
D.
hasNeighboringLanguages
Indicates that two languages are geographically or regionally adjacent to each other in their areas of use.
-
E.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35568767c819084d5e18b56a4745e |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f5eabe88190a12b244ea71e46d6 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:30 p.m.