Triple
T1332159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liga MX |
E28666
|
entity |
| Predicate | professionalSince |
P27330
|
FINISHED |
| Object | 1943 |
—
|
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: 1943 | Statement: [Liga MX, professionalSince, 1943]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalSince Context triple: [Liga MX, professionalSince, 1943]
-
A.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
B.
professionalHead
Indicates that one entity serves as the primary professional leader or chief authority over another entity within an organizational or occupational context.
-
C.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
D.
isPro
Indicates that an entity is a professional or expert in a particular field, activity, or domain.
-
E.
professionServed
Indicates that an entity has performed work or provided services in a particular profession or occupational role.
- F. None of above. chosen
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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1e7f1388190a6e4eb65a7997380 |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4beef6a188190996f8775bdda8f6c |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0b1326081909aa6beec0cfe8d6c |
completed | March 1, 2026, 10:41 p.m. |
Created at: March 1, 2026, 7:55 p.m.