Triple
T20163706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Griffon |
E491776
|
entity |
| Predicate | rowCountPerTrain |
P138900
|
FINISHED |
| Object | 3 |
—
|
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 | Statement: [Griffon, rowCountPerTrain, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rowCountPerTrain Context triple: [Griffon, rowCountPerTrain, 3]
-
A.
trainCount
Indicates the number of trains associated with a given entity, context, or time period.
-
B.
vehiclesPerTrain
Indicates the number of vehicles that are attached to or make up a single train.
-
C.
trainsPerSide
Indicates the number of trains allocated or operating on each side (e.g., direction, platform, or segment) within a system or configuration.
-
D.
rowsPerCar
Indicates the number of rows associated with or allocated to each individual car.
-
E.
numberOfRailwayTracks
Indicates the quantity of railway tracks associated with or present at a given entity or location.
- F. None of above. chosen
Provenance (4 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66841b7d88190af3606f762d87b24 |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:35 p.m.