Triple
T15910207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2023 East Palestine, Ohio train derailment |
E385828
|
entity |
| Predicate | numberOfCarsDerailed |
P121022
|
FINISHED |
| Object | approximately 38 |
—
|
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: approximately 38 | Statement: [2023 East Palestine, Ohio train derailment, numberOfCarsDerailed, approximately 38]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCarsDerailed Context triple: [2023 East Palestine, Ohio train derailment, numberOfCarsDerailed, approximately 38]
-
A.
numberOfTrainsInvolved
Indicates the count of trains that are involved in a particular event, situation, or incident.
-
B.
speedAtDerailmentApprox
Indicates the approximate speed an entity was traveling at the moment it derailed.
-
C.
vehiclesPerTrain
Indicates the number of vehicles that are attached to or make up a single train.
-
D.
numberOfTrailerCarsBuilt
Indicates the total count of trailer cars that have been constructed.
-
E.
railCarries
Indicates that a rail or railway system transports or conveys a specified entity from one place to another.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:52 a.m.