Triple
T14463148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thermantia |
E358635
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Serena |
E358633
|
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: Serena | Statement: [Thermantia, mother, Serena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serena Context triple: [Thermantia, mother, Serena]
-
A.
Serena
chosen
Serena was a prominent noblewoman of the late Western Roman Empire, known as the influential wife of the powerful general Stilicho and a member of the imperial Theodosian dynasty.
-
B.
Serena
Serena is one of Elle Woods’ bubbly and supportive Delta Nu sorority sisters in the Broadway musical adaptation of "Legally Blonde."
-
C.
Serena
Serena is a central character in George Gershwin's opera "Porgy and Bess," known as a strong, devout woman who provides emotional and moral support within the Catfish Row community.
-
D.
Serena
"Serena" is a 2014 period drama film directed by Susanne Bier, starring Jennifer Lawrence and Bradley Cooper as a married couple whose timber empire unravels in Depression-era North Carolina.
-
E.
Serena
Serena is a feminine given name commonly used in various cultures, often associated with calmness and serenity.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91ad67bc81908ecdaa7262f6dc55 |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a3bade48190a4608ca46f5f558a |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 10, 2026, 1:19 a.m.