Triple
T17398317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiara |
E423011
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Claire |
—
|
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: Claire | Statement: [Chiara, relatedName, Claire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claire Context triple: [Chiara, relatedName, Claire]
-
A.
Claire
Claire is a fictional character named in the work "Lucky Lady," likely serving as one of its central figures.
-
B.
Claire
Claire is a feminine given name of French origin meaning "clear" or "bright," commonly used in English-speaking countries.
-
C.
Claire
Claire is the central protagonist of the film "Intimacy," around whom the story’s emotional and relational tensions revolve.
-
D.
Claire
Claire is a character from the family comedy film "World's Greatest Dad," which stars Robin Williams as a struggling writer and single father.
-
E.
Claire
Claire is a character from the children's book "Picture Day," likely depicted as a young student navigating the small dramas and excitement surrounding school picture day.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43abf7ea08190a9d9f9358e3bb684 |
completed | April 19, 2026, 2:15 a.m. |
Created at: April 10, 2026, 5:45 a.m.