Triple
T1770109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lycian |
E38854
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Milyan |
E37898
|
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: Milyan | Statement: [Lycian, closelyRelatedTo, Milyan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Milyan Context triple: [Lycian, closelyRelatedTo, Milyan]
-
A.
Milyan
chosen
Milyan is an extinct Anatolian Indo-European language once spoken in southwestern Asia Minor, known primarily from a small corpus of inscriptions.
-
B.
Mille
Mille is a French surname most notably borne by individuals such as Stéphane Mille.
-
C.
Manyika
Manyika is a major dialect of the Shona language spoken primarily in eastern Zimbabwe and adjacent areas of Mozambique.
-
D.
Mella
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
-
E.
Micali
Micali is an Italian surname most notably associated with Silvio Micali, a Turing Award–winning computer scientist and cryptographer.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648eb9488190b1be2d2b6d259634 |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9936f5881909b78bda48039916a |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:31 p.m.