Triple
T6479179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R44 subway cars |
E146145
|
entity |
| Predicate | numberBuiltForSIR |
P2091
|
FINISHED |
| Object | 52 |
—
|
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: 52 | Statement: [R44 subway cars, numberBuiltForSIR, 52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberBuiltForSIR Context triple: [R44 subway cars, numberBuiltForSIR, 52]
-
A.
numberBuilt
chosen
Indicates the total count of items or structures that have been constructed or produced.
-
B.
isBuiltFor
Indicates that one entity is specifically designed, intended, or optimized to serve, support, or accommodate another entity or purpose.
-
C.
ISONumber
Indicates that an entity is associated with, identified by, or conforms to a specific ISO (International Organization for Standardization) number or standard.
-
D.
isNumberedBy
Indicates that an entity is assigned, identified, or organized by a specific number or numbering scheme.
-
E.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a4e764c819086828bb841f588e0 |
completed | March 22, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:51 p.m.