Triple
T10547162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saba |
E248850
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Marib Dam |
E224611
|
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: Marib Dam | Statement: [Saba, knownFor, Marib Dam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marib Dam Context triple: [Saba, knownFor, Marib Dam]
-
A.
Marib Dam
chosen
Marib Dam is an ancient and historically significant irrigation dam in Yemen, considered one of the great engineering achievements of the pre-Islamic Arabian world.
-
B.
Daivões Dam
Daivões Dam is a hydroelectric dam located on Portugal’s Tâmega River, forming part of the Tâmega electroproduction system.
-
C.
Roza Dam
Roza Dam is a diversion dam on Washington State’s Yakima River that helps supply irrigation water as part of the U.S. Bureau of Reclamation’s Yakima Project.
-
D.
Hatnur Dam
Hatnur Dam is a major irrigation and flood-control dam built on the Tapi River in Maharashtra, India.
-
E.
Solina Dam
Solina Dam is a major hydroelectric and flood-control dam in southeastern Poland, known for creating the large artificial Solina Lake in the Bieszczady region.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d526d20ef48190ab9f70d4ce5f2a11 |
completed | April 7, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9344a53fc81909765061d07d0cd20 |
completed | April 10, 2026, 5:32 p.m. |
Created at: April 6, 2026, 12:33 p.m.