Triple
T95689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Organization for Migration |
E1924
|
entity |
| Predicate | hasFieldOffices |
P1268
|
FINISHED |
| Object | worldwide |
—
|
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: worldwide | Statement: [International Organization for Migration, hasFieldOffices, worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFieldOffices Context triple: [International Organization for Migration, hasFieldOffices, worldwide]
-
A.
hasOffice
chosen
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
B.
establishedOffice
Indicates that an entity created or set up an official office or place of operation.
-
C.
headquartersLocation
Indicates the place where an organization’s main administrative center or principal office is located.
-
D.
limitsOffice
Indicates that one entity imposes a restriction or cap on the scope, duration, or powers of another entity’s office or official position.
-
E.
hasClerk
Indicates that an entity is served, assisted, or managed by a clerk associated with it.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.