Triple
T23122928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seejiq |
E576948
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Tgdaya dialect
The Tgdaya dialect is a regional variety of the Seediq (Seejiq) language spoken by an Indigenous community in Taiwan.
|
E1570898
|
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: Tgdaya dialect | Statement: [Seejiq, hasDialect, Tgdaya dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tgdaya dialect Context triple: [Seejiq, hasDialect, Tgdaya dialect]
-
A.
Tigapanah dialect
The Tigapanah dialect is a regional variety of the Karo Batak language spoken by Karo communities in and around the Tigapanah area of North Sumatra, Indonesia.
-
B.
Tappalang dialect
The Tappalang dialect is a regional variety of the Mandar language spoken by Mandar communities in parts of West Sulawesi, Indonesia.
-
C.
Lempur dialect
The Lempur dialect is a regional variety of the Kerinci language spoken in and around the village of Lempur in Jambi, Sumatra, Indonesia.
-
D.
Yagwa dialect
The Yagwa dialect is a regional variety of the Masa language spoken by communities in parts of Central Africa.
-
E.
Taai dialect
The Taai dialect is a regional variety of the Saisiyat language spoken by the indigenous Saisiyat people of Taiwan.
- 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: Tgdaya dialect Triple: [Seejiq, hasDialect, Tgdaya dialect]
Generated description
The Tgdaya dialect is a regional variety of the Seediq (Seejiq) language spoken by an Indigenous community in Taiwan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tgdaya dialect Target entity description: The Tgdaya dialect is a regional variety of the Seediq (Seejiq) language spoken by an Indigenous community in Taiwan.
-
A.
Tigapanah dialect
The Tigapanah dialect is a regional variety of the Karo Batak language spoken by Karo communities in and around the Tigapanah area of North Sumatra, Indonesia.
-
B.
Tappalang dialect
The Tappalang dialect is a regional variety of the Mandar language spoken by Mandar communities in parts of West Sulawesi, Indonesia.
-
C.
Lempur dialect
The Lempur dialect is a regional variety of the Kerinci language spoken in and around the village of Lempur in Jambi, Sumatra, Indonesia.
-
D.
Yagwa dialect
The Yagwa dialect is a regional variety of the Masa language spoken by communities in parts of Central Africa.
-
E.
Taai dialect
The Taai dialect is a regional variety of the Saisiyat language spoken by the indigenous Saisiyat people of Taiwan.
- 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_69e245f6c2e881909a228fdcfeb7c7d3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e517a0481909829a73fdf255d1c |
completed | April 29, 2026, 4:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c23f25dec8190984bc2dafd008a48 |
completed | May 19, 2026, 8:48 a.m. |
| NEDg | Description generation | batch_6a0c271e8a8c8190ba994f557f077288 |
completed | May 19, 2026, 9:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c27d3befc8190bc7a3697bc0e817b |
completed | May 19, 2026, 9:05 a.m. |
Created at: April 17, 2026, 3:59 p.m.