Triple
T6795457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GB |
E156042
|
entity |
| Predicate | alpha2Code |
P208
|
FINISHED |
| Object | GB |
E156042
|
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: GB | Statement: [GB, alpha2Code, GB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GB Context triple: [GB, alpha2Code, GB]
-
A.
GB
chosen
GB is the ISO 3166-1 alpha-2 country code for the United Kingdom of Great Britain and Northern Ireland.
-
B.
GB
GB is the regional code for Gilgit-Baltistan, a mountainous administrative territory in northern Pakistan known for its high peaks and strategic location.
-
C.
GB
GB is the common abbreviation for Gençlerbirliği S.K., a professional football club based in Ankara, Turkey.
-
D.
GB
GB is a major generative grammar framework in linguistics developed by Noam Chomsky that explains how sentences are structured in the human mind.
-
E.
GA
GA is the commonly used abbreviation for General Atomics, an American energy and defense corporation known for its work in nuclear technology and unmanned aerial vehicles.
- 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_69c6881844448190a65822d9b39d7f88 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2c6e7dc8190b1f33372d047baba |
completed | March 27, 2026, 6:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a9354448190890846c2e84bb22c |
completed | March 28, 2026, 12:02 a.m. |
Created at: March 27, 2026, 2:15 p.m.