Triple
T10606394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian python |
E275886
|
entity |
| Predicate | binomialName |
P569
|
FINISHED |
| Object | Python molurus |
E633579
|
NE 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: Python molurus | Statement: [Indian python, binomialName, Python molurus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Python molurus Context triple: [Indian python, binomialName, Python molurus]
-
A.
IT-MOL
IT-MOL is the Italian region code for Molise, a small region in southern Italy.
-
B.
Mol
Mol is a municipality in the Belgian region of Flanders known for its lakes, nature reserves, and recreational tourism.
-
C.
Pythonoidea
chosen
Pythonoidea is a superfamily of non-venomous constrictor snakes that includes pythons and their closest relatives.
-
D.
Molek
Molek is a deity from ancient Near Eastern religions, often associated with child sacrifice and condemned in the Hebrew Bible.
-
E.
Mayavi
Mayavi is a 3D scientific data visualization library for Python, widely used for interactive plotting and analysis of complex numerical data.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4b7aa48190bf7873b293571030 |
completed | April 8, 2026, 11:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95eb726bc8190a8db7357bd126016 |
completed | April 10, 2026, 8:33 p.m. |
Created at: April 8, 2026, 7:32 p.m.