Triple
T18330462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alyssa |
E439124
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Alicia |
—
|
NE NERFINISHED |
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: Alicia | Statement: [Alyssa, relatedTo, Alicia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alicia Context triple: [Alyssa, relatedTo, Alicia]
-
A.
Alicia
Alicia is the given name of the American singer, songwriter, and pianist Alicia Keys, known for her soulful R&B music and powerful vocals.
-
B.
Alicia
Alicia is a fictional character associated with the entity or concept known as "The Lonely."
-
C.
Alicia
Alicia is a supporting character in the Argentine-Spanish film "Martín (Hache)," involved in the complex emotional and interpersonal dynamics surrounding the protagonist.
-
D.
Alicia
Alicia is a central female character in the 2017 Southern Gothic thriller "The Beguiled," whose complex emotions and shifting loyalties help drive the film’s tense, atmospheric drama.
-
E.
Alicia
Alicia is the central protagonist of "The Demolitionist," around whom the film’s action and narrative primarily revolve.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (2 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ec900808190bc4468270e0957c1 |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.