Triple
T5075281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabel |
E114378
|
entity |
| Predicate | isCognateWith |
P2527
|
FINISHED |
| Object | Izabela |
E496543
|
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: Izabela | Statement: [Isabel, isCognateWith, Izabela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Izabela Context triple: [Isabel, isCognateWith, Izabela]
-
A.
Izabel
chosen
Izabel is a feminine given name, commonly used in various cultures as a variant of Isabel or Isabella.
-
B.
Terézia
Terézia is the given name of the Hungarian-born German writer and translator Terézia Mora, known for her award-winning novels and screenplays.
-
C.
Elisabeta
Elisabeta is a given name used in various European languages, corresponding to the English name Elizabeth.
-
D.
Kunegunda
Kunegunda is a feminine given name of Polish origin, historically borne by European nobility such as Theresa Kunegunda Sobieska.
-
E.
Isabella
Isabella is a virtuous and resourceful young noblewoman in Horace Walpole’s Gothic novel "The Castle of Otranto," whose peril and resistance drive much of the story’s suspense and drama.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74d2243481908c1ae62f7123c4e9 |
completed | March 20, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becfb9bcf48190acac2714c25de725 |
completed | March 21, 2026, 5:04 p.m. |
Created at: March 20, 2026, 1:39 p.m.