Triple
T23601280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | southern elephant seal |
E582763
|
entity |
| Predicate | maximumMaleLength |
P49297
|
FINISHED |
| Object | about 6 metres |
—
|
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 6 metres | Statement: [southern elephant seal, maximumMaleLength, about 6 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumMaleLength Context triple: [southern elephant seal, maximumMaleLength, about 6 metres]
-
A.
maximumMaleBodyLength
chosen
Indicates the greatest recorded body length measured for male individuals of a given entity or species.
-
B.
maximumFemaleBodyLength
Indicates the greatest recorded length of the body for female individuals of a given entity or group.
-
C.
maximumAdultLength
Indicates the greatest length an organism or entity can reach at full adult size.
-
D.
maleLength
Indicates that the relationship specifies the length or size measurement of a male individual or male part of an entity.
-
E.
hornLengthMale
Indicates the measured length of the horns specifically for male individuals 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_69e248faa2788190abb1581742daa6aa |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b0936f588190aead4419aedfcb0e |
completed | April 29, 2026, 7:17 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:43 p.m.