Triple
T74734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libya |
E1495
|
entity |
| Predicate | recognizedLanguage |
P238
|
FINISHED |
| Object |
Tebu
Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
|
E6206
|
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: Tebu | Statement: [Libya, recognizedLanguage, Tebu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tebu Context triple: [Libya, recognizedLanguage, Tebu]
-
A.
Culebra
Culebra is a small Caribbean island municipality of Puerto Rico known for its pristine beaches, clear waters, and protected wildlife refuges.
-
B.
Lick
Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
-
C.
Gori
Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
-
D.
Mango
Mango is a sweet, tropical stone fruit widely cultivated and consumed around the world, especially in South Asia.
-
E.
Boric
Boric is the surname of Gabriel Boric, the Chilean politician who became one of the world’s youngest heads of state when he was elected President of Chile.
- 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: Tebu Triple: [Libya, recognizedLanguage, Tebu]
Generated description
Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tebu Target entity description: Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
-
A.
Culebra
Culebra is a small Caribbean island municipality of Puerto Rico known for its pristine beaches, clear waters, and protected wildlife refuges.
-
B.
Namba
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
-
C.
Mouton
Mouton is an academic publishing house known for its influential works in linguistics and related fields.
-
D.
Koba
Koba was a revolutionary alias used by Joseph Stalin during his early political activities in the Bolshevik movement.
-
E.
Lick
Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f1b99a48190aec004ecd49b4a0d |
completed | Feb. 28, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2554ffb8c8190a30aceecd7f30d96 |
completed | Feb. 28, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_69a25943cba88190a78f708d453ce968 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a259c2706c8190b5319c004e207c29 |
completed | Feb. 28, 2026, 2:58 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.