Triple

T23929254
Position Surface form Disambiguated ID Type / Status
Subject Politécnico–Pantitlán E602445 entity
Predicate hasRollingStock P1305 FINISHED
Object Mexico City Metro NM-02
Mexico City Metro NM-02 is a series of rubber-tyred electric multiple unit trains used on Line 5 of the Mexico City Metro system.
 E1607730 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: Mexico City Metro NM-02 | Statement: [Politécnico–Pantitlán, hasRollingStock, Mexico City Metro NM-02]
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: Mexico City Metro NM-02
Triple: [Politécnico–Pantitlán, hasRollingStock, Mexico City Metro NM-02]
Generated description
Mexico City Metro NM-02 is a series of rubber-tyred electric multiple unit trains used on Line 5 of the Mexico City Metro system.

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_69e2953b928c819095395fa87baca583 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cf9a18248190b20991969921ecfd completed April 29, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f764349e48190af6b5ba1d06a638f completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f77372e188190bbf5c1a77de0833c completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77d47ea08190828e5f5f9f0e3899 completed May 21, 2026, 9:23 p.m.
Created at: April 17, 2026, 8:55 p.m.