Triple

T31196847
Position Surface form Disambiguated ID Type / Status
Subject Tazoult E795345 entity
Predicate hasArchaeologicalSite P1098 FINISHED
Object Roman ruins of Lambaesis
The Roman ruins of Lambaesis are the remains of a major Roman military camp and settlement in present-day Algeria, notable for its well-preserved legionary fortress, temples, and public buildings.
 E1951144 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: Roman ruins of Lambaesis | Statement: [Tazoult, hasArchaeologicalSite, Roman ruins of Lambaesis]
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: Roman ruins of Lambaesis
Triple: [Tazoult, hasArchaeologicalSite, Roman ruins of Lambaesis]
Generated description
The Roman ruins of Lambaesis are the remains of a major Roman military camp and settlement in present-day Algeria, notable for its well-preserved legionary fortress, temples, and public buildings.

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_69f224d7a6a481908187c4362a8a525f completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69bbedcbc8190b1b45ec966db581f completed May 3, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29591a77208190b67d2a8c5f161130 completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a295f49d9048190bddbefd68a0d3a29 completed June 10, 2026, 12:57 p.m.
NED2 Entity disambiguation (via description) batch_6a295fa1c9688190b5483526ef6959ae completed June 10, 2026, 12:59 p.m.
Created at: April 29, 2026, 9:09 p.m.