Triple
T12690723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halkapınar |
E303195
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | İzmir Metro |
E62383
|
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: İzmir Metro | Statement: [Halkapınar, servedBy, İzmir Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: İzmir Metro Context triple: [Halkapınar, servedBy, İzmir Metro]
-
A.
Izmir Metro
chosen
Izmir Metro is a rapid transit rail system serving the city of Izmir, Turkey, providing high-capacity urban transportation across key districts.
-
B.
Istanbul Metro
The Istanbul Metro is a rapid transit system serving Istanbul, Turkey, connecting key districts and transport hubs across the city.
-
C.
İzmir Metro Basmane station
İzmir Metro Basmane station is an underground rapid transit stop in central İzmir that provides metro access and interchange with the adjacent historic Basmane railway station.
-
D.
Ankara Metro
Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
-
E.
Tram Izmir
Tram Izmir is a modern light rail tram network serving the Turkish city of İzmir as part of its urban public transportation system.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961dabb38819087738361f9de8066 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684e2292c8190bffb3a8b6e15029c |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:22 p.m.