Triple
T14934439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George |
E372351
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object | Geo |
E100419
|
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: Geo | Statement: [George, hasShortForm, Geo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geo Context triple: [George, hasShortForm, Geo]
-
A.
Geo
Geo was a defunct General Motors automobile brand from the late 1980s and 1990s that specialized in small, economy cars often built in partnership with foreign manufacturers.
-
B.
Geo
chosen
Geo is a short form of the given name Georges, often used as an informal or familiar nickname.
-
C.
GEOC
GEOC is the commonly used abbreviation for the Division of Geochemistry, a professional group focused on the study of the chemical composition and processes of the Earth.
-
D.
GEO
GEO is the three-letter ISO 3166-1 alpha-3 country code representing the nation of Georgia.
-
E.
GEO
GEO is an intergovernmental partnership that coordinates global efforts to build and improve Earth observation systems for informed environmental and societal decision-making.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded647ae388190a0e97c03f2a4d832 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5a6135481908b0d49b0f4060c98 |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 2:37 a.m.