Triple
T4554692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longreads |
E120451
|
entity |
| Predicate | contentLength |
P266
|
FINISHED |
| Object | long-form |
—
|
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: long-form | Statement: [Longreads, contentLength, long-form]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentLength Context triple: [Longreads, contentLength, long-form]
-
A.
maximumBodyLength
Indicates that there is an upper limit on the allowable length or size of a body (e.g., content, message, or object) in this relationship or action.
-
B.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
C.
hasBodyLengthRange
Indicates the range of possible body lengths associated with an entity, typically expressed as a minimum and maximum value.
-
D.
IVLength
Indicates the measured length of an intravenous (IV) line or catheter used in a medical context.
-
E.
totalSystemLength
Indicates the complete measured length of an entire system, aggregating all its relevant components or segments.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd58127ed08190a04962a43afb888b |
completed | March 20, 2026, 2:22 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.