Triple
T14196293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farshut |
E351843
|
entity |
| Predicate | isoCountryCode |
P208
|
FINISHED |
| Object | EG |
E1032109
|
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: EG | Statement: [Farshut, isoCountryCode, EG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EG Context triple: [Farshut, isoCountryCode, EG]
-
A.
EG
EG is the standard abbreviation for the Egmont Group, an international network of Financial Intelligence Units that collaborates to combat money laundering and terrorist financing.
-
B.
EG
EG is the standard abbreviation for the European Games, a continental multi-sport event for athletes from across Europe.
-
C.
EG
chosen
EG is the ISO 3166-1 alpha-2 country code for Egypt, a transcontinental nation in North Africa and the Middle East known for its ancient civilization and monuments like the Pyramids of Giza.
-
D.
GER
GER is the IATA airport code for Rafael Cabrera Mustelier Airport, which serves Nueva Gerona on Cuba’s Isla de la Juventud.
-
E.
GER
GER is the official FIFA country code used to represent the Germany national football team in international competitions and records.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e1fbd48190a4864fa4443f8f29 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd194b32d88190aa74eef576152db3 |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 10, 2026, 1:04 a.m.