Triple
T6127621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Legislative Assemblies |
E136631
|
entity |
| Predicate | canHaveSmallerSize |
P68033
|
FINISHED |
| Object | by Parliament law for some states |
—
|
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: by Parliament law for some states | Statement: [State Legislative Assemblies, canHaveSmallerSize, by Parliament law for some states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canHaveSmallerSize Context triple: [State Legislative Assemblies, canHaveSmallerSize, by Parliament law for some states]
-
A.
hasMinimumSize
Indicates that an entity meets or exceeds a specified minimum size threshold.
-
B.
smallerThan
Indicates that one entity has a strictly lesser size, dimension, or magnitude than another entity.
-
C.
isSmallestOf
Indicates that an entity has the minimum size or value within a specified set or group of entities.
-
D.
isSmall
Indicates that one entity has a size that is relatively small, either in absolute terms or compared to a reference standard or another entity.
-
E.
includesSizeRange
Indicates that one entity specifies or covers a particular range of sizes associated with another entity.
- 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_69c008a0a37c81908e5b4f879158afb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c2a13a48190b80e11d58fc87c8a |
completed | March 22, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69c049fa905c8190b99eda54e9771b0b |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:15 p.m.