Triple

T36429532
Position Surface form Disambiguated ID Type / Status
Subject Municipality of Progreso E897403 entity
Predicate containsSettlement P847 FINISHED
Object San Ignacio, Yucatán
San Ignacio, Yucatán is a small locality in the Mexican state of Yucatán, situated near the Gulf coast within the municipality of Progreso.
E2186589 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: San Ignacio, Yucatán | Statement: [Municipality of Progreso, containsSettlement, San Ignacio, Yucatán]
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: San Ignacio, Yucatán
Triple: [Municipality of Progreso, containsSettlement, San Ignacio, Yucatán]
Generated description
San Ignacio, Yucatán is a small locality in the Mexican state of Yucatán, situated near the Gulf coast within the municipality of Progreso.

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_69f76e559b10819099d6655a6e14587c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd5041648190978f88d3b55d6f71 completed May 3, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39dbc0b298819084f3a404da033a26 completed June 23, 2026, 1:05 a.m.
NEDg Description generation batch_6a39dc5a50148190b2ee1baa102027bd completed June 23, 2026, 1:07 a.m.
NED2 Entity disambiguation (via description) batch_6a39dce5e4c881908b8dcb4d77bc2227 completed June 23, 2026, 1:09 a.m.
Created at: May 3, 2026, 4:10 p.m.