Triple
T24840787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red de Jóvenes por México |
E621606
|
entity |
| Predicate | hasSuborganizations |
P148778
|
FINISHED |
| Object | municipal youth committees |
—
|
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: municipal youth committees | Statement: [Red de Jóvenes por México, hasSuborganizations, municipal youth committees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuborganizations Context triple: [Red de Jóvenes por México, hasSuborganizations, municipal youth committees]
-
A.
hasSubOrganizationType
Indicates that an organization is associated with or classified under a specific type or category of sub-organization.
-
B.
hasAuxiliaryOrganizations
Indicates that an entity is associated with one or more subsidiary or supporting organizations that assist or extend its activities.
-
C.
hasNumberOfSisterOrganizations
Indicates the count of sister or peer organizations associated with a given organization.
-
D.
hasSubsidiaryBusiness
Indicates that one business entity owns or controls another business entity as its subsidiary.
-
E.
hasOrganizations
chosen
Indicates that an entity is associated with, linked to, or includes one or more organizations.
- 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_69e2fac185d48190a0a6073ad1f6b792 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
Created at: April 18, 2026, 5:18 a.m.