Triple
T16606211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christo |
E403453
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Gabrovo, Bulgaria |
E343154
|
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: Gabrovo, Bulgaria | Statement: [Christo, birthPlace, Gabrovo, Bulgaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabrovo, Bulgaria Context triple: [Christo, birthPlace, Gabrovo, Bulgaria]
-
A.
Gabrovo
chosen
Gabrovo is a town in central Bulgaria known for its humor and satire traditions, as well as its historical role in the country’s industrial development.
-
B.
Pazardzhik, Bulgaria
Pazardzhik is a city in southern Bulgaria known as a regional administrative and cultural center on the banks of the Maritsa River.
-
C.
Dimitrovgrad, Bulgaria
Dimitrovgrad, Bulgaria is an industrial town in southern Bulgaria known for its planned socialist-era architecture and location near the Maritsa River.
-
D.
Blagoevgrad
Blagoevgrad is a city in southwestern Bulgaria known as a regional cultural and educational center, home to several universities and a vibrant student population.
-
E.
Sapareva Banya
Sapareva Banya is a Bulgarian spa town renowned for its hot mineral springs and the hottest geyser in continental Europe.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36090cf388190b401c55230912104 |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0075a8a6248190a9e2bb469d821c66 |
completed | May 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 5:17 a.m.