Triple
T38414281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meteor Crater |
E901562
|
entity |
| Predicate | impactorEstimatedMass |
P7301
|
FINISHED |
| Object | about 300,000 tons |
—
|
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: about 300,000 tons | Statement: [Meteor Crater, impactorEstimatedMass, about 300,000 tons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactorEstimatedMass Context triple: [Meteor Crater, impactorEstimatedMass, about 300,000 tons]
-
A.
impactor
Indicates that one entity exerts a forceful contact or collision upon another, typically causing a physical impact or change.
-
B.
impactorType
Indicates the kind or category of object or agent that causes an impact or collision in the relationship.
-
C.
impactorDiameter
Indicates the size of the object that impacts another body, typically measured as the diameter of the impacting body.
-
D.
approximateMass
chosen
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
-
E.
impactorName
Indicates the name or identifier assigned to the entity that causes an impact or collision in the relationship.
- 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_69f76e61e79c81908b787d83b46ab92b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: May 3, 2026, 4:31 p.m.