Triple
T15833301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | صندوق الاستثمارات العامة |
E383923
|
entity |
| Predicate | مجال_الاستثمار |
P45042
|
FINISHED |
| Object | البنية التحتية |
—
|
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: البنية التحتية | Statement: [صندوق الاستثمارات العامة, مجال_الاستثمار, البنية التحتية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مجال_الاستثمار Context triple: [صندوق الاستثمارات العامة, مجال_الاستثمار, البنية التحتية]
-
A.
investment
Indicates a relationship where one party allocates resources (such as money, time, or effort) into something with the expectation of future benefit or return.
-
B.
investmentScope
chosen
Indicates the range or boundaries of activities, assets, or sectors that an investment is intended or allowed to cover.
-
C.
vestments
Indicates that one entity is wearing or is ceremonially clothed in special religious or official garments associated with a role or office.
-
D.
investsIn
Indicates that one entity allocates resources, typically money or capital, into another entity with the expectation of future returns or benefits.
-
E.
investmentGeography
Indicates the geographic region or location where an investment is targeted, managed, or primarily focused.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e6670d48190a456581dd951f168 |
completed | April 16, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.