Triple
T8010346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haʻapai |
E186472
|
entity |
| Predicate | largestSettlement |
P163
|
FINISHED |
| Object | Pangai |
E707319
|
NE FINISHED |
How this triple was built (2 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: Pangai | Statement: [Haʻapai, largestSettlement, Pangai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pangai Context triple: [Haʻapai, largestSettlement, Pangai]
-
A.
Pangai
chosen
Pangai is the main administrative and population center of the Haʻapai island group in the Kingdom of Tonga.
-
B.
Pongau
Pongau is a mountainous district in the Austrian state of Salzburg, known for its Alpine landscapes, ski resorts, and traditional towns.
-
C.
Pangnirtung
Pangnirtung is a small Inuit hamlet on Baffin Island in Nunavut, Canada, known for its dramatic Arctic landscapes, traditional culture, and renowned printmaking and weaving arts.
-
D.
Pegau
Pegau is a small historic town in the German state of Saxony, known for its medieval architecture and location near Leipzig.
-
E.
Panglao
Panglao is a popular island municipality in the Philippines known for its white-sand beaches, diving spots, and tourism-oriented resorts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d70caf8819090a9f98025470c0d |
completed | March 31, 2026, 3:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63c1f76881909ad6d7777090f2e2 |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:19 p.m.