Triple
T7554750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primos |
E178632
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Aldan |
E129692
|
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: Aldan | Statement: [Primos, adjacentTo, Aldan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aldan Context triple: [Primos, adjacentTo, Aldan]
-
A.
Aldan
chosen
Aldan is a mining town in Russia’s Sakha Republic known for its significant gold deposits and remote Siberian location.
-
B.
Nadym
Nadym is a town in the Yamalo-Nenets Autonomous Okrug of Russia, known as a regional center for the natural gas industry and served by its own airport.
-
C.
Nain
Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
-
D.
Nain
Nain is a renowned Iranian town famous for producing high-quality, finely knotted Persian carpets characterized by intricate designs and a typically light color palette.
-
E.
Andoolo
Andoolo is a small town that serves as an administrative center in the Indonesian province of Southeast Sulawesi.
- 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_69c69f2da22c8190a50942ac20af70e8 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8b990148190b26a3a262cf538b3 |
completed | March 27, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856be6e1c8190ba292d4d9cf1f37f |
completed | March 28, 2026, 10:31 p.m. |
Created at: March 27, 2026, 3:49 p.m.