Triple
T9045652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George |
E216747
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Georgie |
E97024
|
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: Georgie | Statement: [George, hasDiminutive, Georgie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgie Context triple: [George, hasDiminutive, Georgie]
-
A.
Georgina
Georgina is a feminine given name used in various English-speaking and European countries, often considered a variant of Georgia or the feminine form of George.
-
B.
Georgina
Georgina is a lakeside town in Ontario, Canada, known for its recreational waterfront communities and proximity to Lake Simcoe.
-
C.
Georgy
chosen
Georgy is a masculine given name of Russian origin, notably borne by Soviet military commander Georgy Zhukov.
-
D.
Georgette
Georgette is a comic servant character in Molière’s play "L’École des femmes," known for her earthy wit and role in highlighting the play’s social and gender tensions.
-
E.
Sophie
Sophie is a feminine given name of Greek origin, commonly used in many countries and meaning "wisdom."
- 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_69ca83d22d488190adbce5e020e9cd1d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6b148b188190814d64acae493634 |
completed | April 1, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfebada5948190add8813ba547647f |
completed | April 3, 2026, 4:32 p.m. |
Created at: March 30, 2026, 7:09 p.m.