Triple
T1666074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai International Circuit |
E36014
|
entity |
| Predicate | lengthMi |
P266
|
FINISHED |
| Object | 3.387 |
—
|
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: 3.387 | Statement: [Shanghai International Circuit, lengthMi, 3.387]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthMi Context triple: [Shanghai International Circuit, lengthMi, 3.387]
-
A.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
B.
properLengthMeasuredIn
Indicates that the proper (intrinsic or rest-frame) length of an entity is expressed using a specified unit of measurement.
-
C.
lengthVariesBy
Indicates that the length of one entity changes or differs depending on another specified factor or condition.
-
D.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
E.
lengthInWords
Indicates the number of words that make up the length of something, typically a text or expression.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.