Triple
T19927117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akhmeteli–Varketili Line |
E478952
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
300 Aragveli station
300 Aragveli station is a metro station on the Tbilisi Metro system in Georgia, serving passengers on the Akhmeteli–Varketili Line.
|
E1403142
|
NE FINISHED |
How this triple was built (4 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: 300 Aragveli station | Statement: [Akhmeteli–Varketili Line, hasStation, 300 Aragveli station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 300 Aragveli station Context triple: [Akhmeteli–Varketili Line, hasStation, 300 Aragveli station]
-
A.
Zoravar Andranik station
Zoravar Andranik station is a central underground station on the Yerevan Metro system in Armenia’s capital city.
-
B.
Sasuntsi Davit station
Sasuntsi Davit station is a metro station in Yerevan, Armenia, named after the Armenian folk hero David of Sasun and serving as a key stop on the city's metro system.
-
C.
Gortsaranayin station
Gortsaranayin station is a metro station on the Yerevan Metro system in Yerevan, Armenia.
-
D.
Serdika station
Serdika station is a central interchange station in the Sofia Metro system, connecting key lines and serving as a major transit hub in Bulgaria’s capital.
-
E.
Chilonzor station
Chilonzor station is a metro station on the Tashkent Metro system in Tashkent, Uzbekistan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 300 Aragveli station Triple: [Akhmeteli–Varketili Line, hasStation, 300 Aragveli station]
Generated description
300 Aragveli station is a metro station on the Tbilisi Metro system in Georgia, serving passengers on the Akhmeteli–Varketili Line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 300 Aragveli station Target entity description: 300 Aragveli station is a metro station on the Tbilisi Metro system in Georgia, serving passengers on the Akhmeteli–Varketili Line.
-
A.
Zoravar Andranik station
Zoravar Andranik station is a central underground station on the Yerevan Metro system in Armenia’s capital city.
-
B.
Sasuntsi Davit station
Sasuntsi Davit station is a metro station in Yerevan, Armenia, named after the Armenian folk hero David of Sasun and serving as a key stop on the city's metro system.
-
C.
Gortsaranayin station
Gortsaranayin station is a metro station on the Yerevan Metro system in Yerevan, Armenia.
-
D.
Serdika station
Serdika station is a central interchange station in the Sofia Metro system, connecting key lines and serving as a major transit hub in Bulgaria’s capital.
-
E.
Chilonzor station
Chilonzor station is a metro station on the Tashkent Metro system in Tashkent, Uzbekistan.
- F. None of above. chosen
Provenance (5 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659ca52c881908dc8053bf61be4c4 |
completed | April 20, 2026, 4:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07f6e1e0308190bdc79950739d83f3 |
completed | May 16, 2026, 4:47 a.m. |
| NEDg | Description generation | batch_6a07f8cbaab88190816f279bb29e27f2 |
completed | May 16, 2026, 4:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07f95e72788190ad4105dc21af48b6 |
completed | May 16, 2026, 4:58 a.m. |
Created at: April 10, 2026, 1:53 p.m.