Triple
T4904691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mephibosheth |
E109885
|
entity |
| Predicate | hasSon |
P6882
|
FINISHED |
| Object | Mica |
E478993
|
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: Mica | Statement: [Mephibosheth, hasSon, Mica]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mica Context triple: [Mephibosheth, hasSon, Mica]
-
A.
Mica
chosen
Mica is a biblical figure mentioned in the Old Testament as a descendant of King Saul through Mephibosheth.
-
B.
Mimili
Mimili is a remote Aboriginal community in South Australia, home primarily to Pitjantjatjara people and known for its strong cultural traditions and art.
-
C.
Miaja
Miaja is a Spanish surname most notably associated with General José Miaja, a key Republican military leader during the Spanish Civil War.
-
D.
Miki
Miki is a city in Japan located within Hyogo Prefecture, known for its traditional hardware industry and historical sites.
-
E.
Mimi
Mimi is a common affectionate diminutive or nickname for the given name Marie.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e71a5c481909f5862bf497c3c9d |
completed | March 20, 2026, 3:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be779c47348190bd8e19f87c2aa4c2 |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:29 p.m.