Triple

T26662805
Position Surface form Disambiguated ID Type / Status
Subject Chelas station E666694 entity
Predicate openedWithSection P75924 FINISHED
Object Alameda–Oriente section of Red Line
The Alameda–Oriente section of the Red Line is a segment of the Lisbon Metro network that includes stations such as Chelas and connects central Lisbon to the eastern Oriente area.
 E1735661 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: Alameda–Oriente section of Red Line | Statement: [Chelas station, openedWithSection, Alameda–Oriente section of Red Line]
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: Alameda–Oriente section of Red Line
Triple: [Chelas station, openedWithSection, Alameda–Oriente section of Red Line]
Generated description
The Alameda–Oriente section of the Red Line is a segment of the Lisbon Metro network that includes stations such as Chelas and connects central Lisbon to the eastern Oriente area.

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_69ee9cf8c7188190b9b00270a8a89164 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f616c0a7bc8190bb57f83858b4f7fb completed May 2, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec4c93888190898e4b06371513c5 completed May 23, 2026, 6:05 p.m.
NEDg Description generation batch_6a11edc0dcb881909cf23e6303439681 completed May 23, 2026, 6:11 p.m.
NED2 Entity disambiguation (via description) batch_6a11eee584a48190aa152f30f2c59f69 completed May 23, 2026, 6:16 p.m.
Created at: April 27, 2026, 2:37 a.m.