Triple
T8397280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menua |
E198085
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Menua |
E198085
|
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: Menua | Statement: [Menua, name, Menua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Menua Context triple: [Menua, name, Menua]
-
A.
Menua
chosen
Menua was a prominent king of the ancient kingdom of Urartu, known for expanding its territory and developing extensive irrigation and fortification projects.
-
B.
Tarro
Tarro is a suburban railway station in the Hunter Region of New South Wales, Australia, serving the local community on the Main Northern line.
-
C.
Mandulis
Mandulis is a Nubian sun god venerated in the region of Lower Nubia, particularly during the Greco-Roman period.
-
D.
Meatu
Meatu is a rural district and administrative settlement in northern Tanzania’s Simiyu Region, known for its agriculture and livestock-keeping communities.
-
E.
Farino
Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb818893348190a6ea2ff6a2e3e491 |
completed | March 31, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde867d21c8190b066a6c88273ec5a |
completed | April 2, 2026, 3:54 a.m. |
Created at: March 30, 2026, 6:04 p.m.