Triple
T30857725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Minister to Liberia |
E785972
|
entity |
| Predicate | rankComparedToAmbassador |
P126996
|
FINISHED |
| Object | lower than ambassador |
—
|
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: lower than ambassador | Statement: [United States Minister to Liberia, rankComparedToAmbassador, lower than ambassador]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankComparedToAmbassador Context triple: [United States Minister to Liberia, rankComparedToAmbassador, lower than ambassador]
-
A.
rankComparedToCabinetMinister
Indicates how an entity’s rank or status compares relative to that of a cabinet minister.
-
B.
rankComparedTo
Indicates the relative ordering or position of one entity in comparison to another based on a specified ranking criterion.
-
C.
diplomaticRankRelative
chosen
Indicates the relative seniority or hierarchical ranking between two diplomatic positions or titles.
-
D.
rankComparedToCount
Indicates how an entity’s rank or ordering position compares relative to a specified total count or number of items.
-
E.
rankWithinOrganization
Indicates the relative hierarchical position or level an entity holds within a specific organization.
- 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_69f224b91c14819084e764832fe67a57 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f691a5995081909ec37fc167c286d0 |
completed | May 3, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:46 p.m.