Triple
T770024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Practical Zionism |
E16260
|
entity |
| Predicate | viewsAsPrimaryMeans |
P9353
|
FINISHED |
| Object | settlement and labor |
—
|
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: settlement and labor | Statement: [Practical Zionism, viewsAsPrimaryMeans, settlement and labor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewsAsPrimaryMeans Context triple: [Practical Zionism, viewsAsPrimaryMeans, settlement and labor]
-
A.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
-
B.
viewsOnPrimacy
chosen
Indicates a relationship where one party expresses or holds a particular stance on the importance or precedence of something relative to other things.
-
C.
hasPrimarySee
Indicates that one entity is designated as the main or preferred "see" reference or cross-reference for another entity.
-
D.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
E.
primaryUser
Indicates that the referenced user is the main or principal user associated with a given account, resource, or context.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a70376988190be2826259f5281ab |
completed | March 1, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69a4a508c42c8190850a0ac7844a3ea9 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.