Triple
T6688648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aralle-Tabulahan language |
E152165
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Tabulahan
Tabulahan is a dialect of the Aralle-Tabulahan language spoken by a local community in West Sulawesi, Indonesia.
|
E610792
|
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: Tabulahan | Statement: [Aralle-Tabulahan language, hasDialect, Tabulahan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabulahan Context triple: [Aralle-Tabulahan language, hasDialect, Tabulahan]
-
A.
Tababela
Tababela is a rural parish in the Quito Metropolitan District of Ecuador, known for hosting the city’s main air gateway, Mariscal Sucre International Airport.
-
B.
Tábua
Tábua is a municipality in central Portugal known for its rural landscapes, traditional villages, and location between the Mondego and Alva rivers.
-
C.
Tabuelan
Tabuelan is a coastal municipality in the province of Cebu in the Philippines, known for its beaches and rural, laid-back atmosphere.
-
D.
The Table
The Table is a distinctive flat-topped volcanic mesa located in Garibaldi Provincial Park in British Columbia, Canada.
-
E.
The Table
"The Table" is the English name of Surah Al-Ma'idah, a chapter of the Qur'an that addresses themes of lawful and unlawful food, covenants, and adherence to divine law.
- 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: Tabulahan Triple: [Aralle-Tabulahan language, hasDialect, Tabulahan]
Generated description
Tabulahan is a dialect of the Aralle-Tabulahan language spoken by a local community in West Sulawesi, Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tabulahan Target entity description: Tabulahan is a dialect of the Aralle-Tabulahan language spoken by a local community in West Sulawesi, Indonesia.
-
A.
Tababela
Tababela is a rural parish in the Quito Metropolitan District of Ecuador, known for hosting the city’s main air gateway, Mariscal Sucre International Airport.
-
B.
Tábua
Tábua is a municipality in central Portugal known for its rural landscapes, traditional villages, and location between the Mondego and Alva rivers.
-
C.
Tabuelan
Tabuelan is a coastal municipality in the province of Cebu in the Philippines, known for its beaches and rural, laid-back atmosphere.
-
D.
The Table
"The Table" is the English name of Surah Al-Ma'idah, a chapter of the Qur'an that addresses themes of lawful and unlawful food, covenants, and adherence to divine law.
-
E.
The Table
The Table is a distinctive flat-topped volcanic mesa located in Garibaldi Provincial Park in British Columbia, Canada.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b14feb28819097bc157df8a2f96e |
completed | March 27, 2026, 4:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7b31fa0819089c4debbbbce9d22 |
completed | March 27, 2026, 9:33 p.m. |
| NEDg | Description generation | batch_69c6f8d27d388190816cfeefbe1519d8 |
completed | March 27, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f9729d7881908f3c396690ffcae8 |
completed | March 27, 2026, 9:41 p.m. |
Created at: March 27, 2026, 2:04 p.m.