Triple
T9414804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinsukia |
E226989
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Makum |
E686755
|
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: Makum | Statement: [Tinsukia, hasNearbyTown, Makum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makum Context triple: [Tinsukia, hasNearbyTown, Makum]
-
A.
Makum
chosen
Makum is a notable town in Assam, India, recognized historically as a coal-mining and railway hub within the Tinsukia district.
-
B.
Makye
"Makye" is the debut studio album by Ghanaian rapper Sarkodie, widely credited with helping to popularize his career and modern hiplife music.
-
C.
Ummanz
Ummanz is a small German Baltic Sea island located just off the western coast of Rügen, known for its rural landscape and bird-rich wetlands.
-
D.
Munduk
Munduk is a scenic highland village in northern Bali, Indonesia, known for its cool climate, lush coffee and clove plantations, and numerous waterfalls.
-
E.
Makokou
Makokou is a small town in northeastern Gabon that serves as a key access point to the surrounding rainforest and protected areas.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c7bd648190b17f082883c98239 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107b63cf48190a072e3434a7b85a8 |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:47 p.m.