Triple
T6927454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sipakapense |
E160347
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object |
Sipacapa
Sipacapa is a highland municipality in the San Marcos department of western Guatemala, known for its predominantly Sipakapense Maya population and traditional indigenous culture.
|
E631854
|
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: Sipacapa | Statement: [Sipakapense, region, Sipacapa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sipacapa Context triple: [Sipakapense, region, Sipacapa]
-
A.
Pacasmayo
Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
-
B.
Ogáxpa
Ogáxpa is the traditional name used by the Quapaw people to refer to themselves or their community in their own language.
-
C.
Gachancipá
Gachancipá is a municipality in the Cundinamarca Department of Colombia, located in the central highlands near Bogotá.
-
D.
Achacachi
Achacachi is a town in Bolivia known as a commercial and cultural center of the Aymara people near Lake Titicaca.
-
E.
Papico
Papico is a popular Japanese squeezable ice cream treat known for its twin plastic tube packaging and creamy, milkshake-like texture.
- 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: Sipacapa Triple: [Sipakapense, region, Sipacapa]
Generated description
Sipacapa is a highland municipality in the San Marcos department of western Guatemala, known for its predominantly Sipakapense Maya population and traditional indigenous culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sipacapa Target entity description: Sipacapa is a highland municipality in the San Marcos department of western Guatemala, known for its predominantly Sipakapense Maya population and traditional indigenous culture.
-
A.
Pacasmayo
Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
-
B.
Ogáxpa
Ogáxpa is the traditional name used by the Quapaw people to refer to themselves or their community in their own language.
-
C.
Gachancipá
Gachancipá is a municipality in the Cundinamarca Department of Colombia, located in the central highlands near Bogotá.
-
D.
Achacachi
Achacachi is a town in Bolivia known as a commercial and cultural center of the Aymara people near Lake Titicaca.
-
E.
Papico
Papico is a popular Japanese squeezable ice cream treat known for its twin plastic tube packaging and creamy, milkshake-like texture.
- 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da1bf2088190a8ccfa01d9a1efc5 |
completed | March 27, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c75859735081909382f1542271a1e4 |
completed | March 28, 2026, 4:26 a.m. |
| NEDg | Description generation | batch_69c75a417b7481908846a53712ea2323 |
completed | March 28, 2026, 4:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c75abf8de881908e1ae0a46da795bc |
completed | March 28, 2026, 4:36 a.m. |
Created at: March 27, 2026, 2:27 p.m.