Triple

T33070463
Position Surface form Disambiguated ID Type / Status
Subject Maaten al-Sarra airbase E846221 entity
Predicate namedAfter P63 FINISHED
Object Maaten al-Sarra area
Maaten al-Sarra area is a remote desert region in southeastern Libya near the border with Sudan and Chad, known for its strategic military significance.
E2033842 NE FINISHED

How this triple was built (2 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: Maaten al-Sarra area | Statement: [Maaten al-Sarra airbase, namedAfter, Maaten al-Sarra area]
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: Maaten al-Sarra area
Triple: [Maaten al-Sarra airbase, namedAfter, Maaten al-Sarra area]
Generated description
Maaten al-Sarra area is a remote desert region in southeastern Libya near the border with Sudan and Chad, known for its strategic military significance.

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_69f3495405b88190967af2157b43b896 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d3ae7a1881909ca47eff098b0724 completed May 3, 2026, 4:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34e529cf888190a255bca80f80bcf4 completed June 19, 2026, 6:43 a.m.
NEDg Description generation batch_6a34e5b49a648190aca8b4ea64bb77da completed June 19, 2026, 6:46 a.m.
NED2 Entity disambiguation (via description) batch_6a34e66fc7fc81908758e4f67ce150b4 completed June 19, 2026, 6:49 a.m.
Created at: May 1, 2026, 1:25 a.m.