Triple
T7840487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İzmir Province |
E181790
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Gaziemir |
E285088
|
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: Gaziemir | Statement: [İzmir Province, contains, Gaziemir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaziemir Context triple: [İzmir Province, contains, Gaziemir]
-
A.
Gaziemir
chosen
Gaziemir is a district of İzmir, Turkey, known for its proximity to the city’s main international airport and its role as a growing residential and commercial hub.
-
B.
Kasimov
Kasimov is a historic town in central Russia known for its Tatar heritage, medieval architecture, and location on the Oka River.
-
C.
Gudermes
Gudermes is a town in the Chechen Republic of Russia that serves as an important regional transport and administrative center.
-
D.
Demerdzhi
Demerdzhi is a notable mountain massif in Crimea, famous for its striking rock formations and scenic landscapes.
-
E.
Zangezur
Zangezur is a mountainous historical region in the South Caucasus, largely corresponding to today’s Syunik Province in southern Armenia and parts of neighboring territories.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c589748190b34d0911d373e194 |
completed | March 31, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdf0394348190b5928ffb9e3df45e |
completed | March 31, 2026, 2:49 p.m. |
Created at: March 30, 2026, 4:47 p.m.