Triple
T1749862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chelonia mydas |
E38414
|
entity |
| Predicate | maximumMass |
P14792
|
FINISHED |
| Object | over 180 kilograms |
—
|
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: over 180 kilograms | Statement: [Chelonia mydas, maximumMass, over 180 kilograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumMass Context triple: [Chelonia mydas, maximumMass, over 180 kilograms]
-
A.
maximumWeight
chosen
Indicates the greatest allowable or observed weight value associated with an entity or relationship.
-
B.
maximumPayload
Indicates the greatest amount of load or capacity that an entity is designed or allowed to carry, handle, or support.
-
C.
hasMass_kg
Indicates that an entity possesses a specific mass measured in kilograms.
-
D.
maximumTakeoffWeight
Indicates the greatest allowable weight an aircraft can have at the start of its takeoff roll under specified conditions.
-
E.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.