Triple
T5779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the United States |
E112
|
entity |
| Predicate | predecessorOffice |
P97
|
FINISHED |
| Object | President of the Continental Congress |
—
|
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: President of the Continental Congress | Statement: [President of the United States, predecessorOffice, President of the Continental Congress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorOffice Context triple: [President of the United States, predecessorOffice, President of the Continental Congress]
-
A.
predecessor
chosen
Indicates that one entity comes before another in an ordered sequence or succession.
-
B.
formerName
Indicates that an entity was previously known by a different name in the past.
-
C.
successor
Indicates that one entity directly follows another in an ordered sequence or position.
-
D.
leftOffice
Indicates that an entity ceased holding or performing the duties of a particular office or position.
-
E.
wasSupersededBy
Indicates that one entity has been replaced or made obsolete by another entity that takes over its role or function.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23ae754fc8190812506055ce94672 |
completed | Feb. 28, 2026, 12:46 a.m. |
| PD | Predicate disambiguation | batch_69a239997f888190bf941b74fbc9c15f |
completed | Feb. 28, 2026, 12:40 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.