Triple
T5363931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catalogue of Women |
E103084
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Mestra |
E250364
|
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: Mestra | Statement: [Catalogue of Women, featuresCharacter, Mestra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mestra Context triple: [Catalogue of Women, featuresCharacter, Mestra]
-
A.
Mestra
chosen
Mestra is a figure in Greek mythology, daughter of King Erysichthon, known for being granted the power of shape-shifting by Poseidon.
-
B.
Marisus
Marisus is the historical Latin name for the Mureș River, a major waterway flowing through present-day Romania and Hungary.
-
C.
Amorina
Amorina is a 19th-century Swedish novel by Carl Jonas Love Almqvist, known for its romantic and psychological depth within early modern Swedish literature.
-
D.
Leonessa
Leonessa is a historic mountain town in central Italy, known for its medieval architecture and scenic location in the Apennines.
-
E.
Massandra
Massandra is a resort settlement near Yalta in Crimea, best known for its historic winery and palace.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865d42508190a1a96121674c1020 |
completed | March 20, 2026, 5:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf21f2bc708190b596c5402fa07e75 |
completed | March 21, 2026, 10:55 p.m. |
Created at: March 20, 2026, 2:02 p.m.