Triple
T18280127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wexner Israel Fellowship at Harvard Kennedy School |
E437841
|
entity |
| Predicate | participantNationality |
P99870
|
FINISHED |
| Object | Israeli |
—
|
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: Israeli | Statement: [Wexner Israel Fellowship at Harvard Kennedy School, participantNationality, Israeli]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: participantNationality Context triple: [Wexner Israel Fellowship at Harvard Kennedy School, participantNationality, Israeli]
-
A.
hasParticipantNationality
chosen
Indicates that a participant in an event, activity, or relation has a specific nationality.
-
B.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
-
C.
ownerNationality
Indicates that the owner of an entity has the specified nationality.
-
D.
nationalityRepresented
Indicates the country or nation that an entity officially represents, typically in a professional, competitive, or diplomatic capacity.
-
E.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50055d2b88190a10199771f64c4b9 |
completed | April 19, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.