Triple
T11303389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gen language |
E267652
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Mina |
E499507
|
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: Mina | Statement: [Gen language, alternativeName, Mina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mina Context triple: [Gen language, alternativeName, Mina]
-
A.
Mina
chosen
Mina is a Gbe language of the Niger-Congo family spoken primarily in southern Togo and neighboring regions of West Africa.
-
B.
Mina
Mina is a valley and neighborhood near Mecca in Saudi Arabia that serves as a major site for key Hajj rituals, including the symbolic stoning of the devil.
-
C.
Mina
Mina is a coastal city and port in northern Lebanon known for its maritime activities and proximity to Tripoli.
-
D.
Mina
Mina is a feminine given name used in various cultures, often as a short form of names like Wilhelmina, Amina, or Emina.
-
E.
Mahina
Mahina is a coastal commune on the island of Tahiti in French Polynesia, known for its proximity to Point Venus and its scenic Pacific shoreline.
- 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_69e50a57366081908a05fc52c5d4074c |
completed | April 19, 2026, 5:01 p.m. |
Created at: April 8, 2026, 9:32 p.m.