Triple
T16619995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matemale Lake |
E403798
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object | Matemale |
E392507
|
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: Matemale | Statement: [Matemale Lake, nearbySettlement, Matemale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matemale Context triple: [Matemale Lake, nearbySettlement, Matemale]
-
A.
Matemale
chosen
Matemale is a small commune in the Pyrénées-Orientales department of southern France, known for its high-altitude lake and mountain setting in the Capcir plateau.
-
B.
Matabaan
Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
-
C.
Maatkas
Maatkas is a town and commune located in the mountainous Kabylie region of northern Algeria.
-
D.
Matatū
Matatū is a professional New Zealand women's rugby union team that competes in the Super Rugby Aupiki competition.
-
E.
Matalam
Matalam is a municipality in the province of Cotabato on the island of Mindanao in the Philippines, known primarily as an agricultural community.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754c934c8190a0a8ddd747681aa7 |
completed | April 18, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007db0b4348190beb573bc3df98125 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.