Triple
T7888561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 Copiapó mining accident |
E183164
|
entity |
| Predicate | numberOfRescueHolesDrilled |
P60797
|
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: [2010 Copiapó mining accident, numberOfRescueHolesDrilled, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRescueHolesDrilled Context triple: [2010 Copiapó mining accident, numberOfRescueHolesDrilled, 3]
-
A.
numberOfHoles
Indicates the count of holes associated with or present in a given entity.
-
B.
hasDrillHolesFrom
Indicates that an object bears drill holes that were created by another specified entity or process.
-
C.
numberOfBores
chosen
Indicates the relationship specifying how many bores (e.g., cylindrical holes or channels) are present in or associated with an object.
-
D.
numberOfFailedBombs
Indicates the count of bombs associated with an entity that did not successfully detonate or function as intended.
-
E.
numberOfChambers
Indicates the count of distinct chambers or compartments associated with an entity.
- 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_69ca828af6e48190a06ee7010d8f0e64 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39ea8d1c81908ef99569e0cf00b7 |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92b0cd881908e715a10d3252e83 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:59 p.m.