Triple
T3668235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fran |
E77813
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Franny |
E76953
|
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: Franny | Statement: [Fran, relatedName, Franny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franny Context triple: [Fran, relatedName, Franny]
-
A.
Franny
chosen
Franny is a common diminutive or nickname for the given name Frances.
-
B.
Frankie
Frankie is a character from the 2020 supernatural horror film "The Craft: Legacy," which continues the story of teenage witches exploring power and identity.
-
C.
Trudy
Trudy is the nickname of Gertrude Ederle, the American competitive swimmer who became the first woman to swim across the English Channel.
-
D.
Fanny Einstein
Fanny Einstein was a woman known primarily through historical records under her married name, originally born as Fanny Koch.
-
E.
Fay
Fay is a given name most famously associated with Canadian-American actress Fay Wray, the iconic star of the 1933 film "King Kong."
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42997d88190bc765559bd7645fc |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4884e36108190a19887e81921fe32 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.