Triple
T7125192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Code of Civil Procedure, 1908 |
E166041
|
entity |
| Predicate | numberOfOrdersApprox |
P3463
|
FINISHED |
| Object | 51 |
—
|
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: 51 | Statement: [Code of Civil Procedure, 1908, numberOfOrdersApprox, 51]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfOrdersApprox Context triple: [Code of Civil Procedure, 1908, numberOfOrdersApprox, 51]
-
A.
numberOfOrders
chosen
Indicates the total count of orders associated with a given entity or context.
-
B.
orderQuantity
Indicates the specific amount or number of items requested or scheduled in an order transaction.
-
C.
hasOrder
Indicates that one entity possesses, is associated with, or is characterized by a specific order, sequence, or arrangement relative to others.
-
D.
ordersBy
Indicates that one entity arranges, sorts, or sequences another entity according to a specified criterion or set of criteria.
-
E.
averageOrder
Indicates the typical or mean value of orders associated with an entity over a given set or period.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e64c0f688190a9b7482d86c2f033 |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:44 p.m.