Triple
T17175709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michal Young |
E416852
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Michal |
E22906
|
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: Michal | Statement: [Michal Young, givenName, Michal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michal Context triple: [Michal Young, givenName, Michal]
-
A.
Michal
chosen
Michal is a biblical figure, a daughter of King Saul who became the first wife of King David in the Hebrew Bible.
-
B.
Michal
Michal is a mentally impaired and childlike character in Martin McDonagh’s dark play "The Pillowman," whose actions and relationship with his brother Katurian are central to the story’s moral and emotional conflict.
-
C.
Michał
Michał is a Polish given name commonly used for males, equivalent to the English name Michael.
-
D.
Michalina
Michalina is a feminine given name of Slavic origin, commonly used in Polish-speaking countries.
-
E.
Milak
Milak is a border town in India’s Uttar Pradesh state, known as a road-linked crossing point on the route to Afghanistan via Zaranj.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0cec448190b30466628a2ff23f |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0148435f6081909bfc6cc1ef59d971 |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:37 a.m.