Triple
T33389831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebastes goodei |
E855014
|
entity |
| Predicate | maximumReportedAge |
P49304
|
FINISHED |
| Object | at least 30 years |
—
|
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: at least 30 years | Statement: [Sebastes goodei, maximumReportedAge, at least 30 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumReportedAge Context triple: [Sebastes goodei, maximumReportedAge, at least 30 years]
-
A.
maximumAgeInYears
Indicates the highest allowable or observed age, expressed in years, associated with an entity or condition.
-
B.
maximumAgeMa
Indicates that there is a specified maximum age limit applicable to an entity or relationship.
-
C.
typicalMaximumAge
Indicates the usual upper age limit that an entity is expected or allowed to reach under normal conditions.
-
D.
maximumRecordedLifespan
chosen
Indicates the greatest length of time that has ever been recorded for an individual of a given type to live.
-
E.
maximumAgeAtAward
Indicates the highest age a recipient can be (or was) at the time an award is given.
- 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_69f3496d54048190a1cb91fdd7caa6ea |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 1, 2026, 1:35 a.m.