Triple
T35074364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Four Square |
E1011969
|
entity |
| Predicate | hasTypicalDistribution |
P101893
|
FINISHED |
| Object | American cities |
—
|
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: American cities | Statement: [American Four Square, hasTypicalDistribution, American cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalDistribution Context triple: [American Four Square, hasTypicalDistribution, American cities]
-
A.
hasDistributionType
chosen
Indicates the type or pattern of distribution associated with an entity, specifying how something is spread, allocated, or made available.
-
B.
distributionAssumption
Indicates an assumed or specified statistical distribution that underlies a model, variable, or process in the relationship.
-
C.
typicalDegreeDistribution
Indicates that a degree distribution is characteristic or commonly observed for a given type of network or graph.
-
D.
hasTypicalAppearance
Indicates that an entity exhibits the standard or commonly expected visual form or look associated with its kind.
-
E.
hasDistributionFunction
Indicates that an entity is associated with a specific distribution function that characterizes how its values or occurrences are probabilistically or statistically distributed.
- 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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff59b33a38819086cc9aa19b81748b |
completed | May 9, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69ff587758f88190a39c2164341dc554 |
completed | May 9, 2026, 3:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.