Triple
T5050645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippopolis |
E113775
|
entity |
| Predicate | locatedInPresentDay |
P40
|
FINISHED |
| Object | Plovdiv |
E191700
|
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: Plovdiv | Statement: [Philippopolis, locatedInPresentDay, Plovdiv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Plovdiv Context triple: [Philippopolis, locatedInPresentDay, Plovdiv]
-
A.
Plovdiv
chosen
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.
-
B.
Burgas
Burgas is a major Bulgarian city and industrial center on the Black Sea coast, known for its large seaport and role as a key maritime and logistics hub in the region.
-
C.
Pazardzhik
Pazardzhik is a city in southern Bulgaria known as a regional economic and cultural center in the Upper Thracian Plain.
-
D.
Asenovgrad
Asenovgrad is a town in southern Bulgaria known as a gateway to the Rhodope Mountains and a regional center rich in historical and religious landmarks.
-
E.
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.
- 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_69bd44391fc48190a311ce9c826c209b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7425df74819091cfde348dd16a68 |
completed | March 20, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea480fee88190a4302301259f29ba |
completed | March 21, 2026, 2 p.m. |
Created at: March 20, 2026, 1:37 p.m.