Triple
T1847888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trabzon |
E41325
|
entity |
| Predicate | hasMinorityLanguage |
P2267
|
FINISHED |
| Object |
Laz
Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
|
E206171
|
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: Laz | Statement: [Trabzon, hasMinorityLanguage, Laz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laz Context triple: [Trabzon, hasMinorityLanguage, Laz]
-
A.
Lazgi
Lazgi is a vibrant and expressive traditional Uzbek dance known for its rapid hand movements, lively rhythms, and roots in the cultural heritage of the Khorezm region.
-
B.
Chaz
Chaz is a common diminutive or nickname for the given name Charles, often used in English-speaking countries.
-
C.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
D.
Lloyd
Lloyd is the middle name of William Lloyd Garrison, the prominent 19th-century American abolitionist and social reformer.
-
E.
Lou
Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
- 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: Laz Triple: [Trabzon, hasMinorityLanguage, Laz]
Generated description
Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laz Target entity description: Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
-
A.
Lazgi
Lazgi is a vibrant and expressive traditional Uzbek dance known for its rapid hand movements, lively rhythms, and roots in the cultural heritage of the Khorezm region.
-
B.
Chaz
Chaz is a common diminutive or nickname for the given name Charles, often used in English-speaking countries.
-
C.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
D.
Lloyd
Lloyd is the middle name of William Lloyd Garrison, the prominent 19th-century American abolitionist and social reformer.
-
E.
Lou
Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
- 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb05412a08190855ea453d1264ea3 |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9c2e0a081909f521e6f73956239 |
completed | March 8, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69adcaf1917c819090eac27de62494ca |
completed | March 8, 2026, 7:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adcbba64588190aa0ebd2b6f67afa7 |
completed | March 8, 2026, 7:19 p.m. |
Created at: March 4, 2026, 7:33 p.m.