Triple
T803059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office for the Coordination of Humanitarian Affairs |
E17169
|
entity |
| Predicate | fieldPresence |
P21207
|
FINISHED |
| Object | country offices |
—
|
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: country offices | Statement: [Office for the Coordination of Humanitarian Affairs, fieldPresence, country offices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldPresence Context triple: [Office for the Coordination of Humanitarian Affairs, fieldPresence, country offices]
-
A.
fieldPresenceIn
Indicates that something exists or is located within a particular field, area, or domain.
-
B.
requiresPresence
Indicates that one entity’s existence, operation, or validity depends on another entity being present or available.
-
C.
hasHumanPresence
Indicates that humans are physically present in or occupying a given location, object, or context.
-
D.
fieldPattern
Indicates a recurring or structured arrangement or configuration present within a field or area.
-
E.
presentOn
Indicates that one entity is physically located on the surface or within the bounds of another entity.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ace495348190aec66f35ea90bc89 |
completed | March 1, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69a4aa70973c8190adbf08302d1103a9 |
completed | March 1, 2026, 9:06 p.m. |
| PDg | Predicate description generation | batch_69a4ace369b481908ad69de6de99f5e6 |
completed | March 1, 2026, 9:17 p.m. |
Created at: March 1, 2026, 7:38 p.m.