Triple
T30838124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Ambassador to Barbados |
E785420
|
entity |
| Predicate | officeIsPartOf |
P197517
|
FINISHED |
| Object | United States Department of State |
—
|
NE NERFINISHED |
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: United States Department of State | Statement: [United States Ambassador to Barbados, officeIsPartOf, United States Department of State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeIsPartOf Context triple: [United States Ambassador to Barbados, officeIsPartOf, United States Department of State]
-
A.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
-
B.
officeIs
Indicates that one entity serves as the office or official workplace location of another entity.
-
C.
officeItAbbreviatesMemberOf
Indicates that an office-related abbreviation stands for or is a member of a particular office or organizational unit.
-
D.
officeIn
Indicates that one entity has an office located within the premises or jurisdiction of another entity.
-
E.
mentionsOffice
Indicates that one entity explicitly refers to or brings up an office (such as a workplace, office location, or office role) in relation to 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_69f224b73d8c81908129383bfb397c87 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe991bca608190b524e419642f4243 |
completed | May 9, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69fe979fc1c4819091fc48d63ea12063 |
completed | May 9, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69fe991abc6c81908edbb98d61c9ca73 |
completed | May 9, 2026, 2:16 a.m. |
Created at: April 29, 2026, 8:45 p.m.