Triple
T13889523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BPS-3 |
E333932
|
entity |
| Predicate | allowancesType |
P111891
|
FINISHED |
| Object | house rent allowance (where applicable) |
—
|
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: house rent allowance (where applicable) | Statement: [BPS-3, allowancesType, house rent allowance (where applicable)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowancesType Context triple: [BPS-3, allowancesType, house rent allowance (where applicable)]
-
A.
exemptionType
Indicates the specific category or kind of exemption that applies in a given context.
-
B.
allocationType
Indicates the specific manner or category by which resources, responsibilities, or items are assigned or distributed among entities.
-
C.
allows
Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
-
D.
allyType
Indicates that one entity is classified as a specific type or category of ally in relation to another entity.
-
E.
allowsBoarderIncome
Indicates that an entity permits income to be earned or received from taking in boarders (people who pay to live in a room or part of a property).
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a3a24881908d81d634622fbbcc |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:15 p.m.