Triple
T9615380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ley de Migración |
E232204
|
entity |
| Predicate | aplicaEn |
P3306
|
FINISHED |
| Object | territorio de los Estados Unidos Mexicanos |
—
|
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: territorio de los Estados Unidos Mexicanos | Statement: [Ley de Migración, aplicaEn, territorio de los Estados Unidos Mexicanos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aplicaEn Context triple: [Ley de Migración, aplicaEn, territorio de los Estados Unidos Mexicanos]
-
A.
appliesAt
chosen
Indicates that an action, rule, or condition is relevant to or in effect at a specific location, context, or point in time.
-
B.
appliesFrom
Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
-
C.
appliesVia
Indicates that an action, rule, or effect is carried out, implemented, or achieved through a specified method, medium, or mechanism.
-
D.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
E.
appliedAs
Indicates that one entity submitted itself or was put forward for consideration in a particular role, position, or context relative to another 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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9aabb6b88190b53547db885e0129 |
completed | April 1, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69ccd5aa1d2c8190a287bf1cf4a3037e |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:09 p.m.