Triple
T10767752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgie Hyde-Lees |
E253996
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Georgie |
E856584
|
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: [Georgie Hyde-Lees, givenName, Georgie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgie Context triple: [Georgie Hyde-Lees, givenName, Georgie]
-
A.
Georgie
chosen
Georgie is a personal given name used by Ruth Georgie Erica Schrödinger.
-
B.
Georgie
Georgie is a character from the British romantic comedy film "Chalet Girl," which follows a former skateboarding champion working at an upscale ski resort.
-
C.
Georgie Farmer
Georgie Farmer is a British actor best known for his role in the Netflix supernatural comedy-horror series "Wednesday."
-
D.
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.
-
E.
Georgina
Georgina is a lakeside town in Ontario, Canada, known for its recreational waterfront communities and proximity to Lake Simcoe.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7322eb2f08190999e09428e7f7ba8 |
completed | April 9, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de55cbbecc81908c2ddf2739ce7ffe |
completed | April 14, 2026, 2:57 p.m. |
Created at: April 8, 2026, 9:16 p.m.