Triple
T17610340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NTF |
E428949
|
entity |
| Predicate | testSectionCrossSectionArea |
P34936
|
FINISHED |
| Object | about 6.25 square meters |
—
|
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: about 6.25 square meters | Statement: [NTF, testSectionCrossSectionArea, about 6.25 square meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testSectionCrossSectionArea Context triple: [NTF, testSectionCrossSectionArea, about 6.25 square meters]
-
A.
hasCrossSection
Indicates that one entity represents or possesses the cross-sectional shape, profile, or slice of another entity.
-
B.
standardSectionArea
chosen
Indicates that one entity specifies the standard or nominal cross-sectional area associated with another entity.
-
C.
quarterSectionArea
Indicates that one entity specifies the area measurement of a quarter section (one-fourth of a standard land section) associated with another entity.
-
D.
crossesSectionOf
Indicates that one entity passes through or over a specific segment or portion of another entity.
-
E.
coreAreaOf
Indicates that one entity is the central, primary, or most important area or domain of focus for another entity.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2d294881908380b2ab0b4d2503 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:51 a.m.