Triple
T1454971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palestinian national movement |
E31376
|
entity |
| Predicate | seeksResolutionThrough |
P19560
|
FINISHED |
| Object | two-state solution |
—
|
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: two-state solution | Statement: [Palestinian national movement, seeksResolutionThrough, two-state solution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seeksResolutionThrough Context triple: [Palestinian national movement, seeksResolutionThrough, two-state solution]
-
A.
resolutionMethod
Indicates the specific approach, technique, or process used to resolve a problem, conflict, or issue.
-
B.
remedySought
Indicates that a particular legal or corrective action is being requested as a solution or relief in response to a problem or dispute.
-
C.
resolves
Indicates that one entity successfully finds a solution, answer, or outcome for a problem, conflict, or uncertainty involving another entity.
-
D.
resolutionMechanism
Indicates the method, process, or system used to resolve a conflict, issue, or discrepancy between entities.
-
E.
resolutionIdea
chosen
Indicates a proposed method, plan, or approach intended to resolve or address a particular issue, conflict, or problem.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57fead881909a47188ce7312406 |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.