Triple
T20460349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 250th Infantry Division |
E501906
|
entity |
| Predicate | primaryNationalityOfPersonnel |
P130892
|
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: [250th Infantry Division, primaryNationalityOfPersonnel, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryNationalityOfPersonnel Context triple: [250th Infantry Division, primaryNationalityOfPersonnel, Spanish]
-
A.
nationalityOfPersonnel
Indicates the country or countries to which the personnel involved in an activity, organization, or context belong by citizenship or national affiliation.
-
B.
primaryNationality
chosen
Indicates the main national affiliation or citizenship that most strongly characterizes an entity among possibly multiple nationalities.
-
C.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
-
D.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
E.
nationalityOfPersonReferredTo
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a549a48190a1bcd7a6b0f71a11 |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.