Triple
T2478005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States v. Daniel Ellsberg |
E55133
|
entity |
| Predicate | maximumPotentialSentence |
P29667
|
FINISHED |
| Object | over 100 years in prison |
—
|
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: over 100 years in prison | Statement: [United States v. Daniel Ellsberg, maximumPotentialSentence, over 100 years in prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumPotentialSentence Context triple: [United States v. Daniel Ellsberg, maximumPotentialSentence, over 100 years in prison]
-
A.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
B.
maximumNumber
chosen
Indicates that one entity specifies the highest allowable or observed quantity, value, or count associated with another entity.
-
C.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
D.
maximumReach
Indicates the greatest extent, distance, or limit that something can reach or influence within a given context.
-
E.
maximumWeight
Indicates the greatest allowable or observed weight value associated with an entity or relationship.
- 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_69ab49e279e88190ab10d7248aea9d11 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1eb3be481908fa7c6b8f1c78209 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b5e3d481909a5cbc4a96edd24f |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.