Triple
T2286376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tigray Region |
E51399
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Alamata
Alamata is a town in northern Ethiopia that serves as a local commercial and administrative center in the southern part of the Tigray Region.
|
E252972
|
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: Alamata | Statement: [Tigray Region, containsTown, Alamata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alamata Context triple: [Tigray Region, containsTown, Alamata]
-
A.
Alajeró
Alajeró is a small coastal and rural municipality on the island of La Gomera in Spain’s Canary Islands, known for its rugged landscapes and traditional Canarian character.
-
B.
Tarhuna
Tarhuna is a town in northwestern Libya, southeast of Tripoli, known for its strategic role and tribal influence during the Libyan civil conflicts.
-
C.
Al Quoz
Al Quoz is an industrial and residential district in western Dubai known for its warehouses, factories, and growing arts and cultural scene.
-
D.
Barbeya
Barbeya is a monotypic genus of flowering plants comprising a single tree species native to arid regions of East Africa and the Arabian Peninsula.
-
E.
Taiz
Taiz is one of Yemen’s largest and historically most important cities, known as a cultural and intellectual center in the country.
- 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: Alamata Triple: [Tigray Region, containsTown, Alamata]
Generated description
Alamata is a town in northern Ethiopia that serves as a local commercial and administrative center in the southern part of the Tigray Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alamata Target entity description: Alamata is a town in northern Ethiopia that serves as a local commercial and administrative center in the southern part of the Tigray Region.
-
A.
Alajeró
Alajeró is a small coastal and rural municipality on the island of La Gomera in Spain’s Canary Islands, known for its rugged landscapes and traditional Canarian character.
-
B.
Tarhuna
Tarhuna is a town in northwestern Libya, southeast of Tripoli, known for its strategic role and tribal influence during the Libyan civil conflicts.
-
C.
Al Quoz
Al Quoz is an industrial and residential district in western Dubai known for its warehouses, factories, and growing arts and cultural scene.
-
D.
Barbeya
Barbeya is a monotypic genus of flowering plants comprising a single tree species native to arid regions of East Africa and the Arabian Peninsula.
-
E.
Taiz
Taiz is one of Yemen’s largest and historically most important cities, known as a cultural and intellectual center in the country.
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc24730208190af8a5cf443d334f7 |
completed | March 7, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f1b2a7c8190aa836f9feba2ce1a |
completed | March 9, 2026, 8:04 a.m. |
| NEDg | Description generation | batch_69ae8004fb6c81908f9fb1678f608419 |
completed | March 9, 2026, 8:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae809ebfdc8190ae404d5711a58b59 |
completed | March 9, 2026, 8:11 a.m. |
Created at: March 4, 2026, 7:48 p.m.