Triple
T9286582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sus philippensis |
E223407
|
entity |
| Predicate | genus |
P87
|
FINISHED |
| Object | Sus |
E234056
|
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: Sus | Statement: [Sus philippensis, genus, Sus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sus Context triple: [Sus philippensis, genus, Sus]
-
A.
Sus
chosen
Sus is a genus of mammals in the pig family that includes domestic pigs and several species of wild boar.
-
B.
Su
Su is a skilled and deadly martial artist portrayed by Jet Li in the action film "Cradle 2 the Grave."
-
C.
Su
Su is the given name of Su Rogers, a British architect and academic known for her contributions to modern architecture and design education.
-
D.
Su
Su is a Chinese surname borne by many notable historical and contemporary figures, including the Song dynasty poet and statesman Su Shi.
-
E.
Sen
Sen is a common Indian surname, particularly prevalent among Bengali communities and associated with numerous notable figures in academia, arts, and public life.
- 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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0821b1108190b16e9570b09a14de |
completed | April 1, 2026, 11:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0c75b9d308190918f181e13df955a |
completed | April 4, 2026, 8:10 a.m. |
Created at: March 30, 2026, 7:35 p.m.