Triple

T26760286
Position Surface form Disambiguated ID Type / Status
Subject Neighborhood Watch Alliance E674781 entity
Predicate hasMember P10 FINISHED
Object Mary Porter
Mary Porter is a member of the Neighborhood Watch Alliance, a local community group focused on neighborhood safety and vigilance.
 E1753045 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: Mary Porter | Statement: [Neighborhood Watch Alliance, hasMember, Mary Porter]
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: Mary Porter
Triple: [Neighborhood Watch Alliance, hasMember, Mary Porter]
Generated description
Mary Porter is a member of the Neighborhood Watch Alliance, a local community group focused on neighborhood safety and vigilance.

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_69eecda6e9dc81908452fab3ba17ed9b completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f618dce4908190b36b6a0323603e3e completed May 2, 2026, 3:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123a984bbc8190a9aec39751323e61 completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123b7235d081909cc231c0b1cc9b30 completed May 23, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_6a123c1061ac8190b8becdcf391832f8 completed May 23, 2026, 11:45 p.m.
Created at: April 27, 2026, 3:57 a.m.