Triple
T28335968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florencio Ávalos |
E717670
|
entity |
| Predicate | typeOfAccidentExperienced |
P1788
|
FINISHED |
| Object | mining accident |
—
|
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: mining accident | Statement: [Florencio Ávalos, typeOfAccidentExperienced, mining accident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAccidentExperienced Context triple: [Florencio Ávalos, typeOfAccidentExperienced, mining accident]
-
A.
hasAccidentAt
Indicates that an accident involving a subject occurs at a specific location or time.
-
B.
hasModeOfTransportInAccident
Indicates that a specific mode of transport was involved in an accident associated with the given entity.
-
C.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
-
D.
accidentType
chosen
Indicates the specific category or kind of accident associated with an event or incident.
-
E.
accidentOccurredDuring
Indicates that an accident took place within the time span or context of a specified event, activity, or condition.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: April 28, 2026, 12:36 a.m.