Triple
T10578390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big Banana |
E249667
|
entity |
| Predicate | approxLength |
P25800
|
FINISHED |
| Object | about 13 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 13 meters | Statement: [The Big Banana, approxLength, about 13 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxLength Context triple: [The Big Banana, approxLength, about 13 meters]
-
A.
approximateLengthInMeters
chosen
Indicates the estimated or roughly measured length of something expressed in meters.
-
B.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
C.
approximateBlockLength
Indicates that one entity specifies or estimates the length of a block in an approximate or non-exact manner.
-
D.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
E.
approximateCourseLength
Indicates an estimated or rough value for the length or duration of a course rather than an exact measurement.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52756ff1c8190a85022748ca58ba5 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:38 p.m.