Triple
T30656989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nidal Ayyad |
E780411
|
entity |
| Predicate | countryOfCriminalConviction |
P28506
|
FINISHED |
| Object | United States of America |
—
|
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 of America | Statement: [Nidal Ayyad, countryOfCriminalConviction, United States of America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfCriminalConviction Context triple: [Nidal Ayyad, countryOfCriminalConviction, United States of America]
-
A.
countryOfConviction
chosen
Indicates the country in which a person or entity was legally convicted of an offense.
-
B.
countryOfImprisonment
Indicates the country in which a person or entity is or was imprisoned.
-
C.
releasedFromPrisonCountry
Indicates the country in which an entity was released from prison.
-
D.
arrestedInCountry
Indicates that an entity was arrested while located within the jurisdiction of a specified country.
-
E.
placeOfConviction
Indicates the location where a person was formally convicted of a crime or offense.
- 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_69f224a6d10481909290be1a00fc83b3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff9a25407c81909faa86e72a7a9d17 |
completed | May 9, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69ff99c613688190a03b2f93d5ccad2b |
completed | May 9, 2026, 8:32 p.m. |
Created at: April 29, 2026, 8:30 p.m.