Triple
T15984035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kachin Independence Organization |
E387645
|
entity |
| Predicate | headquarters |
P62
|
FINISHED |
| Object |
Laiza
Laiza is a town in northern Myanmar near the Chinese border that serves as the main stronghold and de facto capital of the Kachin Independence Organization.
|
E1188144
|
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: Laiza | Statement: [Kachin Independence Organization, headquarters, Laiza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laiza Context triple: [Kachin Independence Organization, headquarters, Laiza]
-
A.
Sheyla
Sheyla is a feminine given name, typically considered a variant of Sheila or Shayla and used in various cultures.
-
B.
Laís
Laís is a Brazilian given name notably borne by model Laís Ribeiro, recognized for her work with major international fashion brands.
-
C.
Rosana
Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
-
D.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
-
E.
Marcela
Marcela is one of the given names of Alexia Juliana Marcela Laurentien, a member of the Dutch royal family.
- 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: Laiza Triple: [Kachin Independence Organization, headquarters, Laiza]
Generated description
Laiza is a town in northern Myanmar near the Chinese border that serves as the main stronghold and de facto capital of the Kachin Independence Organization.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laiza Target entity description: Laiza is a town in northern Myanmar near the Chinese border that serves as the main stronghold and de facto capital of the Kachin Independence Organization.
-
A.
Sheyla
Sheyla is a feminine given name, typically considered a variant of Sheila or Shayla and used in various cultures.
-
B.
Laís
Laís is a Brazilian given name notably borne by model Laís Ribeiro, recognized for her work with major international fashion brands.
-
C.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
-
D.
Rosana
Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
-
E.
Marcela
Marcela is one of the given names of Alexia Juliana Marcela Laurentien, a member of the Dutch royal family.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15756d6488190ac35da00e96ce21d |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3cdf7848190848e9081027dc027 |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc5669c1c81909bacf61c96cb7816 |
completed | May 9, 2026, 11:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc5c7db1c8190b4e1de6f6e3ce8a0 |
completed | May 9, 2026, 11:39 p.m. |
Created at: April 10, 2026, 4:54 a.m.