Triple
T5457768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1984 Winter Olympics |
E122520
|
entity |
| Predicate | biddingCity |
P7900
|
FINISHED |
| Object | Sofia |
E31299
|
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: Sofia | Statement: [1984 Winter Olympics, biddingCity, Sofia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sofia Context triple: [1984 Winter Olympics, biddingCity, Sofia]
-
A.
Sofia
chosen
Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
-
B.
Sofia
Sofia is a feminine given name of Greek origin, widely used in many cultures and commonly associated with the meaning "wisdom."
-
C.
Sofia
Sofia is a strong-willed, outspoken woman in Alice Walker’s "The Color Purple," known for her resilience and defiance against oppression.
-
D.
Sofya
Sofya is the Russian given name of Sophia Tolstaya, the wife and muse of novelist Leo Tolstoy.
-
E.
Plovdiv
Plovdiv is Bulgaria’s second-largest city and one of Europe’s oldest continuously inhabited urban centers, known for its Roman amphitheater, Old Town, and rich cultural heritage.
- 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd91f1cca48190afa15b8ccfea1f88 |
completed | March 20, 2026, 6:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf41465c3c8190a58350f39d626e54 |
completed | March 22, 2026, 1:09 a.m. |
Created at: March 20, 2026, 2:08 p.m.