Triple
T13073462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capul |
E329510
|
entity |
| Predicate | localLanguage |
P1252
|
FINISHED |
| Object |
Inabaknon
Inabaknon is an Austronesian language spoken primarily on Capul Island in Northern Samar, Philippines, known for its distinctiveness from the surrounding Visayan languages.
|
E1021047
|
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: Inabaknon | Statement: [Capul, localLanguage, Inabaknon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inabaknon Context triple: [Capul, localLanguage, Inabaknon]
-
A.
Nabawan
Nabawan is a rural town and district in the interior of Sabah, Malaysia, known for its indigenous communities and agricultural activities.
-
B.
Kabugao
Kabugao is a dialect of the Isnag language spoken by indigenous communities in the northern Philippines.
-
C.
Kayabacho
Kayabacho is a commercial district in Tokyo's Chūō ward known as a financial hub with dense office buildings and convenient subway access.
-
D.
Ibajay
Ibajay is a coastal municipality in the Philippine province of Aklan known for its mangrove forest and agricultural communities.
-
E.
Nabitasan
Nabitasan is a barangay (village-level administrative division) of the municipality of Oton in the province of Iloilo, Philippines.
- 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: Inabaknon Triple: [Capul, localLanguage, Inabaknon]
Generated description
Inabaknon is an Austronesian language spoken primarily on Capul Island in Northern Samar, Philippines, known for its distinctiveness from the surrounding Visayan languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Inabaknon Target entity description: Inabaknon is an Austronesian language spoken primarily on Capul Island in Northern Samar, Philippines, known for its distinctiveness from the surrounding Visayan languages.
-
A.
Nabawan
Nabawan is a rural town and district in the interior of Sabah, Malaysia, known for its indigenous communities and agricultural activities.
-
B.
Kabugao
Kabugao is a dialect of the Isnag language spoken by indigenous communities in the northern Philippines.
-
C.
Kayabacho
Kayabacho is a commercial district in Tokyo's Chūō ward known as a financial hub with dense office buildings and convenient subway access.
-
D.
Ibajay
Ibajay is a coastal municipality in the Philippine province of Aklan known for its mangrove forest and agricultural communities.
-
E.
Nabitasan
Nabitasan is a barangay (village-level administrative division) of the municipality of Oton in the province of Iloilo, Philippines.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d981160e388190bab942a2ded2903e |
completed | April 10, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d606ac6481908d18a288d5eed472 |
completed | May 3, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69f6dae595908190b27980e48514cda5 |
completed | May 3, 2026, 5:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6db8f68a4819091d8e67d9c8eec81 |
completed | May 3, 2026, 5:22 a.m. |
Created at: April 9, 2026, 9 p.m.