Triple
T2169025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ermita |
E46978
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Malate |
E46066
|
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: Malate | Statement: [Ermita, adjacentTo, Malate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malate Context triple: [Ermita, adjacentTo, Malate]
-
A.
Malate
chosen
Malate is a historic coastal district of Manila, Philippines, known for its nightlife, cultural landmarks, and proximity to Manila Bay.
-
B.
Corachol
Corachol is a subfamily of Uto-Aztecan languages that includes closely related indigenous languages spoken in western Mexico.
-
C.
Comino
Comino is a small, sparsely populated Maltese island in the Mediterranean Sea, best known for its clear waters and the popular Blue Lagoon.
-
D.
Tartegnin
Tartegnin is a small wine-producing municipality in the canton of Vaud in western Switzerland, situated above Lake Geneva in the La Côte region.
-
E.
Glycine
Glycine is a genus of flowering plants in the legume family that includes important species such as the soybean (Glycine max), widely cultivated for food, oil, and animal feed.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeadaed481908d6afa942d7155b8 |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58f26334819095202544d37e6850 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:45 p.m.