Triple
T7035668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funafuti |
E163375
|
entity |
| Predicate | hasLagoon |
P26295
|
FINISHED |
| Object |
Te Namo
Te Namo is the large central lagoon of Funafuti Atoll in Tuvalu, known for its shallow turquoise waters and surrounding coral islets.
|
E637246
|
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: Te Namo | Statement: [Funafuti, hasLagoon, Te Namo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Te Namo Context triple: [Funafuti, hasLagoon, Te Namo]
-
A.
Temanoku
Temanoku is a small settlement located on Nonouti Atoll in the Republic of Kiribati in the central Pacific Ocean.
-
B.
Tanimaiaki
Tanimaiaki is a settlement on the atoll of Abemama in the island nation of Kiribati in the central Pacific Ocean.
-
C.
Nakanamanga
Nakanamanga is an Oceanic Austronesian language spoken primarily on Efate Island and nearby areas in Vanuatu.
-
D.
Taneti Maamau
Taneti Maamau is a Kiribati politician who has served as the country's president, known for his pro-China foreign policy stance and focus on economic development and climate resilience.
-
E.
Zakumi
Zakumi is the leopard-themed mascot character created to represent South Africa and embody the spirit of the 2010 FIFA World Cup.
- 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: Te Namo Triple: [Funafuti, hasLagoon, Te Namo]
Generated description
Te Namo is the large central lagoon of Funafuti Atoll in Tuvalu, known for its shallow turquoise waters and surrounding coral islets.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Te Namo Target entity description: Te Namo is the large central lagoon of Funafuti Atoll in Tuvalu, known for its shallow turquoise waters and surrounding coral islets.
-
A.
Temanoku
Temanoku is a small settlement located on Nonouti Atoll in the Republic of Kiribati in the central Pacific Ocean.
-
B.
Tanimaiaki
Tanimaiaki is a settlement on the atoll of Abemama in the island nation of Kiribati in the central Pacific Ocean.
-
C.
Nakanamanga
Nakanamanga is an Oceanic Austronesian language spoken primarily on Efate Island and nearby areas in Vanuatu.
-
D.
Taneti Maamau
Taneti Maamau is a Kiribati politician who has served as the country's president, known for his pro-China foreign policy stance and focus on economic development and climate resilience.
-
E.
Zakumi
Zakumi is the leopard-themed mascot character created to represent South Africa and embody the spirit of the 2010 FIFA World Cup.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e220508c8190b8950cf38280b8c2 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775a211f88190afe5ed466abcac7a |
completed | March 28, 2026, 6:30 a.m. |
| NEDg | Description generation | batch_69c779c064548190bc17a399723f85e7 |
completed | March 28, 2026, 6:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c77a79e76c8190a42fe57ffc1dc23c |
completed | March 28, 2026, 6:51 a.m. |
Created at: March 27, 2026, 2:36 p.m.