Triple
T1473516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zakat |
E27188
|
entity |
| Predicate | beneficiaryCategory |
P22506
|
FINISHED |
| Object | poor (fuqara) |
—
|
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: poor (fuqara) | Statement: [Zakat, beneficiaryCategory, poor (fuqara)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beneficiaryCategory Context triple: [Zakat, beneficiaryCategory, poor (fuqara)]
-
A.
beneficiaryType
chosen
Indicates the type or category of beneficiary that receives or is intended to receive the benefit or outcome of an action or resource.
-
B.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
-
C.
beneficiaryCountry
Indicates that one country is the recipient or beneficiary of aid, resources, or advantages provided in a given context.
-
D.
beneficiaryRegion
Indicates the region that receives the benefit, advantage, or positive impact resulting from an action, resource, or arrangement.
-
E.
philanthropicBeneficiary
Indicates that one entity is the recipient or target of another entity’s philanthropic giving or charitable support.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.