Triple
T9138173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Latinoamericana, Seguros, S.A. |
E219256
|
entity |
| Predicate | primaryServices |
P11934
|
FINISHED |
| Object | insurance services |
—
|
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: insurance services | Statement: [La Latinoamericana, Seguros, S.A., primaryServices, insurance services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryServices Context triple: [La Latinoamericana, Seguros, S.A., primaryServices, insurance services]
-
A.
primaryService
chosen
Indicates that one entity serves as the main or principal service provided or used in relation to another entity.
-
B.
primaryServes
Indicates that one entity’s main or principal function is to serve, support, or provide service to another entity.
-
C.
primaryServicePattern
Indicates the main or most typical way in which a service is delivered, structured, or utilized within a given context.
-
D.
primaryFor
Indicates that one entity serves as the main or principal option, resource, or association for another entity among possible alternatives.
-
E.
primaryWork
Indicates that one work is the main or most significant work associated with a given entity, as opposed to other secondary or related works.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8efe3b88190a55a15827e6817a4 |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6601d77881908299d58db6e64937 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:19 p.m.