Triple
T2486670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mumbai Monorail |
E55941
|
entity |
| Predicate | numberOfCarsPerTrain |
P14643
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Mumbai Monorail, numberOfCarsPerTrain, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCarsPerTrain Context triple: [Mumbai Monorail, numberOfCarsPerTrain, 4]
-
A.
rowsPerCar
Indicates the number of rows associated with or allocated to each individual car.
-
B.
numberOfCarsPerUnit
chosen
Indicates the quantity of cars associated with each single unit of a specified measure (such as time, distance, or entity).
-
C.
numberOfTrainsInvolved
Indicates the count of trains that are involved in a particular event, situation, or incident.
-
D.
trainCount
Indicates the number of trains associated with a given entity, context, or time period.
-
E.
numberOfRidersPerVehicle
Indicates the quantity of riders associated with each individual vehicle in the relationship.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.