Triple

T34152284
Position Surface form Disambiguated ID Type / Status
Subject Adelaide region E876030 entity
Predicate hasTramway P17788 FINISHED
Object Glenelg tram line
The Glenelg tram line is a historic light rail route in Adelaide, South Australia, linking the city centre with the coastal suburb of Glenelg and serving as one of the region’s key public transport corridors.
E2084665 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: Glenelg tram line | Statement: [Adelaide region, hasTramway, Glenelg tram 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: Glenelg tram line
Triple: [Adelaide region, hasTramway, Glenelg tram line]
Generated description
The Glenelg tram line is a historic light rail route in Adelaide, South Australia, linking the city centre with the coastal suburb of Glenelg and serving as one of the region’s key public transport corridors.

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_69f349abaa508190a820f206620efddc completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70f95ec98819085d82f40bd3425a7 completed May 3, 2026, 9:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36c1cd7f288190a1ea657e560623bd completed June 20, 2026, 4:37 p.m.
NEDg Description generation batch_6a36c27a91288190bf70c5526c0e9354 completed June 20, 2026, 4:40 p.m.
NED2 Entity disambiguation (via description) batch_6a36c332a3a48190b0bfab6d38ef019a completed June 20, 2026, 4:43 p.m.
Created at: May 1, 2026, 1:54 a.m.