Triple
T1749861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chelonia mydas |
E38414
|
entity |
| Predicate | maximumCarapaceLength |
P32114
|
FINISHED |
| Object | about 1.5 meters |
—
|
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 1.5 meters | Statement: [Chelonia mydas, maximumCarapaceLength, about 1.5 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumCarapaceLength Context triple: [Chelonia mydas, maximumCarapaceLength, about 1.5 meters]
-
A.
maximumVesselLength
Indicates the greatest allowable or observed length of a vessel in a given context or constraint.
-
B.
maximumTrunkDiameter
Indicates the largest thickness of a trunk measured across its widest point.
-
C.
baleenLength
Indicates the length of an organism’s baleen structures, typically measured as a physical dimension.
-
D.
largestFigureLengthApprox
Indicates an approximate measurement of the length of the largest figure involved in the relationship or context.
-
E.
weightLimitInPounds
Indicates the maximum allowable weight for something, expressed in pounds.
- 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_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. |
| PDg | Predicate description generation | batch_69ab630cb34881908c9fb7ed5dedcd77 |
completed | March 6, 2026, 11:28 p.m. |
Created at: March 4, 2026, 7:31 p.m.