Triple
T10154936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hámori Lake |
E232750
|
entity |
| Predicate | watercourse |
P415
|
FINISHED |
| Object | Szinva stream |
E215780
|
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: Szinva stream | Statement: [Hámori Lake, watercourse, Szinva stream]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Szinva stream Context triple: [Hámori Lake, watercourse, Szinva stream]
-
A.
Szinva
chosen
Szinva is a small river in northeastern Hungary that flows through the city of Miskolc and is known for features like the Szinva Waterfall.
-
B.
Sîn
Sîn is the Mesopotamian moon god, widely worshipped in ancient Babylonian and Assyrian religion.
-
C.
Sainj
Sainj is a small town in Himachal Pradesh, India, known as a primary access point to the Great Himalayan National Park and the scenic Sainj Valley.
-
D.
Sinis
Sinis is a bandit from Greek mythology, notorious for violently killing travelers by bending and releasing pine trees, who was ultimately slain by the hero Theseus.
-
E.
Sionnan
Sionnan is a figure in Irish mythology associated with the River Shannon, often regarded as the river’s eponymous goddess or origin spirit.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec38f594819088a7eb73fc25feff |
completed | April 2, 2026, 4:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e6541e488190814e6395f219eb12 |
completed | April 5, 2026, 10:46 p.m. |
Created at: March 30, 2026, 9:08 p.m.