Triple

T26884042
Position Surface form Disambiguated ID Type / Status
Subject Harbor region of Los Angeles E676990 entity
Predicate containsNeighborhood P4813 FINISHED
Object Wilmington
Wilmington is a historic industrial and port-adjacent neighborhood in the Harbor region of Los Angeles known for its close ties to the Port of Los Angeles and extensive refinery and shipping facilities.
E364644 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: Wilmington | Statement: [Harbor region of Los Angeles, containsNeighborhood, Wilmington]
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: Wilmington
Triple: [Harbor region of Los Angeles, containsNeighborhood, Wilmington]
Generated description
Wilmington is a historic industrial and port-adjacent neighborhood in the Harbor region of Los Angeles known for its close ties to the Port of Los Angeles and extensive refinery and shipping facilities.

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_69eee9bc0c90819085608c8bdc513a57 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61f61ee6c81908213e768ab561331 completed May 2, 2026, 3:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e84c09c8190950843277718680a completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121ef4122c819085b89773c3408095 completed May 23, 2026, 9:41 p.m.
NED2 Entity disambiguation (via description) batch_6a121f621ab881908dd9d1e675b522ea completed May 23, 2026, 9:42 p.m.
Created at: April 27, 2026, 5:41 a.m.