Triple
T20880621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indaw region |
E514134
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object |
Wuntho
Wuntho is a town in northern Myanmar known historically as the center of the former Wuntho State in the Sagaing Region.
|
E1455571
|
NE FINISHED |
How this triple was built (4 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: Wuntho | Statement: [Indaw region, hasNearbyTown, Wuntho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wuntho Context triple: [Indaw region, hasNearbyTown, Wuntho]
-
A.
Lotha
Lotha is a Naga ethnic group primarily inhabiting the Wokha district of Nagaland in Northeast India, known for its rich cultural traditions and festivals.
-
B.
Thann
Thann is a small historic town in northeastern France, located at the foot of the Vosges mountains in the Haut-Rhin department of Alsace.
-
C.
Sindo
Sindo is an island and administrative division of Ongjin County in Incheon, South Korea, known for its rural landscape and coastal environment.
-
D.
Welun
Welun is the German name for the Polish town of Wieluń, known for being one of the first places bombed at the start of World War II.
-
E.
Rünthe
Rünthe is a former independent locality in North Rhine-Westphalia, Germany, that now forms part of the town of Bergkamen.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wuntho Triple: [Indaw region, hasNearbyTown, Wuntho]
Generated description
Wuntho is a town in northern Myanmar known historically as the center of the former Wuntho State in the Sagaing Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wuntho Target entity description: Wuntho is a town in northern Myanmar known historically as the center of the former Wuntho State in the Sagaing Region.
-
A.
Lotha
Lotha is a Naga ethnic group primarily inhabiting the Wokha district of Nagaland in Northeast India, known for its rich cultural traditions and festivals.
-
B.
Thann
Thann is a small historic town in northeastern France, located at the foot of the Vosges mountains in the Haut-Rhin department of Alsace.
-
C.
Sindo
Sindo is an island and administrative division of Ongjin County in Incheon, South Korea, known for its rural landscape and coastal environment.
-
D.
Welun
Welun is the German name for the Polish town of Wieluń, known for being one of the first places bombed at the start of World War II.
-
E.
Rünthe
Rünthe is a former independent locality in North Rhine-Westphalia, Germany, that now forms part of the town of Bergkamen.
- F. None of above. chosen
Provenance (5 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c67974348190bd3484032c0d7b31 |
completed | April 21, 2026, 12:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0913a46d808190a39fc27ecbb31e99 |
completed | May 17, 2026, 1:02 a.m. |
| NEDg | Description generation | batch_6a09145a9b0481909086941cdd981e1a |
completed | May 17, 2026, 1:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0914f1925081909bce8ad0932c6722 |
completed | May 17, 2026, 1:08 a.m. |
Created at: April 16, 2026, 12:45 p.m.