Triple
T31187857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hijacking of Air France Flight 139 |
E795098
|
entity |
| Predicate | resolvingCountry |
P171232
|
FINISHED |
| Object | Israel |
—
|
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: Israel | Statement: [Hijacking of Air France Flight 139, resolvingCountry, Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resolvingCountry Context triple: [Hijacking of Air France Flight 139, resolvingCountry, Israel]
-
A.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
-
B.
associatedCountryAtTheTime
Indicates the country with which an entity was linked or affiliated during a specific historical time or event, rather than its current or permanent country association.
-
C.
addressedCountry
Indicates that an action, communication, or document is directed or formally addressed to a specific country.
-
D.
registrationCountry
Indicates the country in which an entity is officially registered or incorporated.
-
E.
providerCountry
Indicates the country that serves as the source or origin of the provider in the relationship.
- 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_69f224d675d08190957198068e440422 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c6f01e881908fa84f5d429d37ae |
completed | May 3, 2026, 12:53 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f69c2127088190ae92c72461576d3b |
completed | May 3, 2026, 12:51 a.m. |
Created at: April 29, 2026, 9:08 p.m.