Triple
T10106881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sambar deer |
E216343
|
entity |
| Predicate | genus |
P87
|
FINISHED |
| Object | Rusa |
E227576
|
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: Rusa | Statement: [sambar deer, genus, Rusa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rusa Context triple: [sambar deer, genus, Rusa]
-
A.
Rusa
chosen
Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
-
B.
Russas
Russas is a municipality in the northeastern Brazilian state of Ceará, known for its agricultural activities and semi-arid climate.
-
C.
Rusko
Rusko is a small municipality in southwestern Finland known for its rural character and proximity to the city of Turku.
-
D.
Rus'
Rus' was a medieval East Slavic state that emerged in Eastern Europe and laid the foundations for the later Russian, Ukrainian, and Belarusian nations.
-
E.
Rusguniae
Rusguniae was an important ancient coastal city in the Roman province of Mauretania Caesariensis, located in what is now northern Algeria.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0c8a0408190be886ec1013a5208 |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e59ec83c8190a79fbb0d0de90310 |
completed | April 5, 2026, 10:43 p.m. |
Created at: March 30, 2026, 9:03 p.m.