Triple
T33718247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kufr Aqab |
E863935
|
entity |
| Predicate | hasDeFactoSeparationFrom |
P198634
|
FINISHED |
| Object | rest of Jerusalem |
—
|
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: rest of Jerusalem | Statement: [Kufr Aqab, hasDeFactoSeparationFrom, rest of Jerusalem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDeFactoSeparationFrom Context triple: [Kufr Aqab, hasDeFactoSeparationFrom, rest of Jerusalem]
-
A.
hasSubnationalEntitySeparated
Indicates that a subnational entity has been separated or split off from its original parent jurisdiction.
-
B.
wasDividedAfter
Indicates that one entity was split into parts or separate entities following a specified event or point in time.
-
C.
wasDividedFrom
Indicates that one entity was separated or split off from another entity, resulting in two distinct parts or groups.
-
D.
wasDividedBetween
Indicates that something was partitioned into portions that were allocated to two or more distinct recipients or groups.
-
E.
wasDividedByTreaty
Indicates that an entity (such as a territory or region) was partitioned or separated as the result of a formal treaty or agreement.
- 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_69f34989871c81908682e22a2fe4b829 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
| PDg | Predicate description generation | batch_69fef8c2cdd881908c6f44e4dfa5ffd0 |
completed | May 9, 2026, 9:05 a.m. |
Created at: May 1, 2026, 1:44 a.m.