Triple
T19572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chappaquiddick incident |
E388
|
entity |
| Predicate | accidentType |
P1788
|
FINISHED |
| Object | single-vehicle crash |
—
|
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: single-vehicle crash | Statement: [Chappaquiddick incident, accidentType, single-vehicle crash]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accidentType Context triple: [Chappaquiddick incident, accidentType, single-vehicle crash]
-
A.
accusationType
Indicates the specific category or nature of an accusation made by one party against another.
-
B.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
C.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
-
D.
trafficType
Indicates the category or nature of traffic involved in a given interaction, flow, or connection (e.g., type of network, data, or transport traffic).
-
E.
shipInvolved
Indicates that a ship participates in, is associated with, or plays a role in a specified event or situation.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a24702d4988190a54a4e578b7c919e |
completed | Feb. 28, 2026, 1:38 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.