Triple
T16230181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bubalus quarlesi |
E393956
|
entity |
| Predicate | commonName |
P570
|
FINISHED |
| Object | mountain anoa |
E1184924
|
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: mountain anoa | Statement: [Bubalus quarlesi, commonName, mountain anoa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: mountain anoa Context triple: [Bubalus quarlesi, commonName, mountain anoa]
-
A.
mountain anoa
chosen
The mountain anoa is a small, endangered dwarf buffalo native to the highland forests of Sulawesi, Indonesia.
-
B.
Anomabo
Anomabo is a historic coastal town in Ghana’s Central Region, known for its role in the transatlantic slave trade and its significance to the Fante people.
-
C.
Okapa
Okapa is a rural town in Papua New Guinea known for its highland culture and production of premium coffee.
-
D.
Kuno
Kuno is a masculine given name of German origin, historically borne by various nobles and notable figures in German-speaking regions.
-
E.
Kuno
Kuno is the rebellious central character in E.M. Forster’s dystopian science fiction story "The Machine Stops," who challenges the oppressive, technology-dependent society in which he lives.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d29438c81909aa2724cc47bb959 |
completed | April 17, 2026, 2:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007a0ab08819082aea4c312c9ffc7 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:03 a.m.