Triple
T27260288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Mason |
E687742
|
entity |
| Predicate | patternRange |
P162530
|
FINISHED |
| Object | stripes |
—
|
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: stripes | Statement: [Thomas Mason, patternRange, stripes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: patternRange Context triple: [Thomas Mason, patternRange, stripes]
-
A.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
B.
testRange
Indicates that a value, condition, or behavior is being evaluated to determine whether it falls within a specified range or interval.
-
C.
partOfRange
Indicates that one entity is included within, or constitutes a segment of, the overall extent or span defined by another entity.
-
D.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
E.
rangeDescription
Indicates the span or interval of values, positions, or extents over which something applies or is valid.
- 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_69ef3557abc481908bf3c146f0f3356a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f62b9e5ba88190a3c0d46edec7afe7 |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f625402d808190be8279d895d2b27f |
completed | May 2, 2026, 4:24 p.m. |
Created at: April 27, 2026, 10:52 a.m.