Triple
T31970209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanker |
E816290
|
entity |
| Predicate | appliesToRangeCategory |
P133442
|
FINISHED |
| Object | intercontinental range |
—
|
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: intercontinental range | Statement: [Spanker, appliesToRangeCategory, intercontinental range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToRangeCategory Context triple: [Spanker, appliesToRangeCategory, intercontinental range]
-
A.
hasRangeCategory
chosen
Indicates that a property or measurement falls within a specified category or interval of possible values.
-
B.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
C.
allegedRangeCategory
Indicates that one entity is claimed or suspected to fall within a particular range category defined by another entity or classification.
-
D.
appliesFrom
Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
-
E.
appliesToSegment
Indicates that something is relevant or specifically directed toward a particular segment or subset within a larger whole.
- 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_69f348f5ae5481909da0247869f51955 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fea2d0a4d08190aa06aeb902a02d5a |
completed | May 9, 2026, 2:58 a.m. |
| PD | Predicate disambiguation | batch_69fea24698348190b9b992a8e7cdbcd0 |
completed | May 9, 2026, 2:56 a.m. |
Created at: May 1, 2026, 12:10 a.m.