Triple
T11303503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maritime Region of Togo |
E267654
|
entity |
| Predicate | hasCoastalTown |
P969
|
FINISHED |
| Object | Aného |
E916991
|
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: Aného | Statement: [Maritime Region of Togo, hasCoastalTown, Aného]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aného Context triple: [Maritime Region of Togo, hasCoastalTown, Aného]
-
A.
Aného
chosen
Aného is a historic coastal town in southeastern Togo that once served as the country’s capital and remains an important center of Ewe culture and Atlantic trade heritage.
-
B.
Anezal
Anezal is a village located in the Jbel Sirwa mountain region of southern Morocco.
-
C.
Neka
Neka is a city in northern Iran known for its location near the Caspian Sea and its role as an industrial and agricultural center in Mazandaran Province.
-
D.
Némi
Némi is an Oceanic language spoken by a small indigenous community in New Caledonia.
-
E.
Aneka
Aneka is a skilled Wakandan warrior and former leader of the Dora Milaje in Marvel Comics, known for her defiance of tradition and partnership with fellow warrior Ayo.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a5c3788190ba54eda514b97903 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e525b4bdb88190b22d64eb65e97d9d |
completed | April 19, 2026, 6:57 p.m. |
Created at: April 8, 2026, 9:32 p.m.