Triple
T10481126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sureth |
E247170
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Suret |
E247169
|
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: Suret | Statement: [Sureth, alternativeName, Suret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suret Context triple: [Sureth, alternativeName, Suret]
-
A.
Suret
chosen
Suret is a modern Eastern Neo-Aramaic language spoken primarily by Assyrian communities in parts of Iraq, Syria, Iran, and the global diaspora.
-
B.
Sûre
The Sûre is a river in Western Europe that flows through Belgium and Luxembourg, forming part of the border with Germany and serving as a significant tributary of the Moselle River.
-
C.
Baraut
Baraut is a prominent town in Uttar Pradesh, India, known as a key commercial and administrative center in the Baghpat district.
-
D.
Rasoun
Rasoun is a small town in northern Jordan located within the hilly, forested region of Ajloun Governorate.
-
E.
Durolle
Durolle is a river in central France that flows through the town of Thiers, historically powering its renowned cutlery and knife-making industry.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5095c5dc88190902582db28df01b4 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8a03336988190bc1e61126fe576be |
completed | April 10, 2026, 7:01 a.m. |
Created at: April 6, 2026, 12:22 p.m.