Triple
T19992027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sen’s liberal paradox |
E494085
|
entity |
| Predicate | typicalExampleFeatures |
P5084
|
FINISHED |
| Object | two individuals with preferences over each other’s actions |
—
|
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: two individuals with preferences over each other’s actions | Statement: [Sen’s liberal paradox, typicalExampleFeatures, two individuals with preferences over each other’s actions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalExampleFeatures Context triple: [Sen’s liberal paradox, typicalExampleFeatures, two individuals with preferences over each other’s actions]
-
A.
typicalFeatures
chosen
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
B.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
-
C.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
D.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
E.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe10ffc81908c94168b0a8ea9c9 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:31 p.m.