Triple

T28365973
Position Surface form Disambiguated ID Type / Status
Subject MBTA bus route 8 E718487 entity
Predicate serves P98 FINISHED
Object Harbor Point neighborhood
Harbor Point neighborhood is a waterfront residential area in Boston’s Dorchester district known for its mixed-income housing and proximity to the University of Massachusetts Boston.
 E1813837 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: Harbor Point neighborhood | Statement: [MBTA bus route 8, serves, Harbor Point neighborhood]
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: Harbor Point neighborhood
Triple: [MBTA bus route 8, serves, Harbor Point neighborhood]
Generated description
Harbor Point neighborhood is a waterfront residential area in Boston’s Dorchester district known for its mixed-income housing and proximity to the University of Massachusetts Boston.

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_69eff6ed5af48190be4e0adf298223e0 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64c5645d48190b0c3a2bad5a2e539 completed May 2, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627d42bec819087df30f3cca1d283 completed May 26, 2026, 11:08 p.m.
NEDg Description generation batch_6a1628f366d88190b10dda8b0ab63762 completed May 26, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_6a16297370d08190a0088aa14476bb1f completed May 26, 2026, 11:14 p.m.
Created at: April 28, 2026, 12:55 a.m.