Triple
T16472231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgi |
E400091
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
George
George is a common given name used in many English-speaking and other cultures, historically associated with kings, saints, and notable figures.
|
E372348
|
NE FINISHED |
How this triple was built (4 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: George | Statement: [Georgi, hasVariant, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [Georgi, hasVariant, George]
-
A.
George
George is the given first name of South African rugby union coach Kitch Christie, who led the Springboks to victory in the 1995 Rugby World Cup.
-
B.
George
George is the given first name of Pat Summerall, the famed American sportscaster and former NFL placekicker.
-
C.
George
George is the middle name of William George Barker, a renowned Canadian World War I flying ace and Victoria Cross recipient.
-
D.
George
George is the given name of George Ellery Hale, the influential American solar astronomer and founder of several major observatories.
-
E.
George
George is the given name of George Herbert, 5th Earl of Carnarvon, the British aristocrat who financed the excavation that uncovered Tutankhamun’s tomb.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: George Triple: [Georgi, hasVariant, George]
Generated description
George is a common given name used in many English-speaking and other cultures, historically associated with kings, saints, and notable figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: George Target entity description: George is a common given name used in many English-speaking and other cultures, historically associated with kings, saints, and notable figures.
-
A.
George
George is a male given name commonly used in English-speaking countries and borne by numerous historical figures, including kings, presidents, and cultural icons.
-
B.
George
George is a masculine given name of Greek origin, commonly used in English-speaking countries and borne by numerous historical and contemporary figures.
-
C.
George
George is a common English surname of likely Greek and Latin origin, associated with numerous notable historical and contemporary figures.
-
D.
George
George is a common masculine given name of Greek origin, meaning "farmer" or "earthworker."
-
E.
George
chosen
George is a masculine given name of Greek origin meaning "farmer" or "earthworker," widely used in English-speaking countries and beyond.
- F. None of above.
Provenance (5 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dd19df881909e4562a5e8473338 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a005817fa088190a0eb85016fe5afc4 |
completed | May 10, 2026, 10:04 a.m. |
| NEDg | Description generation | batch_6a0059473c088190a8c9fc757c0a3ef1 |
completed | May 10, 2026, 10:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a005a457868819096e21df6944de0ff |
completed | May 10, 2026, 10:13 a.m. |
Created at: April 10, 2026, 5:11 a.m.