Triple
T16632870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syunik Province |
E404118
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Meghri
Meghri is a small town in southern Armenia known for its mild climate, historic churches, and location near the border with Iran.
|
E1224894
|
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: Meghri | Statement: [Syunik Province, containsCity, Meghri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meghri Context triple: [Syunik Province, containsCity, Meghri]
-
A.
Koghb
Koghb is a village in northeastern Armenia known for its historic churches, archaeological sites, and scenic location near the border with Georgia.
-
B.
Metehara
Metehara is a town in central Ethiopia known for its sugar plantations and proximity to both the Awash National Park and Lake Basaka.
-
C.
Hamra
Hamra is a vibrant, cosmopolitan neighborhood in Beirut, Lebanon, known for its bustling commercial streets, cafes, and cultural life.
-
D.
Shemshak
Shemshak is a mountain village and ski resort in the Alborz range of northern Iran, known for its steep slopes and popularity among advanced skiers.
-
E.
Tsaghkadzor
Tsaghkadzor is a popular Armenian mountain resort town known for its ski slopes, scenic landscapes, and historical monasteries.
- 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: Meghri Triple: [Syunik Province, containsCity, Meghri]
Generated description
Meghri is a small town in southern Armenia known for its mild climate, historic churches, and location near the border with Iran.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meghri Target entity description: Meghri is a small town in southern Armenia known for its mild climate, historic churches, and location near the border with Iran.
-
A.
Koghb
Koghb is a village in northeastern Armenia known for its historic churches, archaeological sites, and scenic location near the border with Georgia.
-
B.
Metehara
Metehara is a town in central Ethiopia known for its sugar plantations and proximity to both the Awash National Park and Lake Basaka.
-
C.
Hamra
Hamra is a vibrant, cosmopolitan neighborhood in Beirut, Lebanon, known for its bustling commercial streets, cafes, and cultural life.
-
D.
Shemshak
Shemshak is a mountain village and ski resort in the Alborz range of northern Iran, known for its steep slopes and popularity among advanced skiers.
-
E.
Tsaghkadzor
Tsaghkadzor is a popular Armenian mountain resort town known for its ski slopes, scenic landscapes, and historical monasteries.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e7d4a48190a9b4a14ecbb2a14b |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007dbe82b4819093b954567790bef7 |
completed | May 10, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_6a007e747eac81908b0b5a2072a177dd |
completed | May 10, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007f75e7e48190ac5cf912cca60d9c |
completed | May 10, 2026, 12:52 p.m. |
Created at: April 10, 2026, 5:17 a.m.