Triple
T4904171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tbilisi Metro |
E109873
|
entity |
| Predicate | connectsDistrict |
P2564
|
FINISHED |
| Object |
Saburtalo
Saburtalo is a major residential and commercial district in Tbilisi, Georgia, known for its Soviet-era apartment blocks, universities, and key transport links.
|
E478963
|
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: Saburtalo | Statement: [Tbilisi Metro, connectsDistrict, Saburtalo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saburtalo Context triple: [Tbilisi Metro, connectsDistrict, Saburtalo]
-
A.
Sironcha
Sironcha is a town in the Gadchiroli district of Maharashtra, India, situated near the confluence of the Pranhita and Godavari rivers.
-
B.
Taborio
Taborio is a village settlement located on the island of Nonouti in the Republic of Kiribati.
-
C.
Rolava
Rolava is a river in the Czech Republic that flows through the Ore Mountains region before joining the Ohře River.
-
D.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
-
E.
Tyrnyauz
Tyrnyauz is a mountainous town in southwestern Russia known for its former tungsten-molybdenum mining industry and location in the North Caucasus.
- 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: Saburtalo Triple: [Tbilisi Metro, connectsDistrict, Saburtalo]
Generated description
Saburtalo is a major residential and commercial district in Tbilisi, Georgia, known for its Soviet-era apartment blocks, universities, and key transport links.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saburtalo Target entity description: Saburtalo is a major residential and commercial district in Tbilisi, Georgia, known for its Soviet-era apartment blocks, universities, and key transport links.
-
A.
Sironcha
Sironcha is a town in the Gadchiroli district of Maharashtra, India, situated near the confluence of the Pranhita and Godavari rivers.
-
B.
Taborio
Taborio is a village settlement located on the island of Nonouti in the Republic of Kiribati.
-
C.
Rolava
Rolava is a river in the Czech Republic that flows through the Ore Mountains region before joining the Ohře River.
-
D.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
-
E.
Tyrnyauz
Tyrnyauz is a mountainous town in southwestern Russia known for its former tungsten-molybdenum mining industry and location in the North Caucasus.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e6fdeac81909092f51ae40ad20e |
completed | March 20, 2026, 3:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fdaaf588190a180d0bf5979c2d2 |
completed | March 21, 2026, 10:15 a.m. |
| NEDg | Description generation | batch_69be70b15c508190bcd723862b8e9633 |
completed | March 21, 2026, 10:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be7139a288819087598a7da8c6ad42 |
completed | March 21, 2026, 10:21 a.m. |
Created at: March 20, 2026, 1:29 p.m.