Triple
T2570617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordanian annexation of the West Bank |
E57656
|
entity |
| Predicate | capitalImpacted |
P10973
|
FINISHED |
| Object | status 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: status of Jerusalem | Statement: [Jordanian annexation of the West Bank, capitalImpacted, status of Jerusalem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capitalImpacted Context triple: [Jordanian annexation of the West Bank, capitalImpacted, status of Jerusalem]
-
A.
affectedCity
chosen
Indicates that a particular city is impacted or influenced by a specified event, action, or condition.
-
B.
economicDamage
Indicates that one entity causes or experiences financial loss, harm, or negative economic impact as a result of another entity or event.
-
C.
lostCapitalTo
Indicates that one entity ceased to be the capital in favor of another entity, to which the capital status was transferred or lost.
-
D.
economicDamageApprox
Indicates that one entity has caused or is associated with an estimated or approximate amount of economic damage to another entity or system.
-
E.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd382928c8190b6316f3db48d8e73 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.