Triple

T35284293

Position	Surface form	Disambiguated ID	Type / Status
Subject	The Fish That Saved Pittsburgh	`E1019032`	entity
Predicate	fictionalTeamName	`P198771`	FINISHED
Object	Pittsburgh Pisces Pittsburgh Pisces is the fictional professional basketball team featured in the 1979 sports comedy film "The Fish That Saved Pittsburgh."	`E2133422`	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: Pittsburgh Pisces | Statement: [The Fish That Saved Pittsburgh, fictionalTeamName, Pittsburgh Pisces]

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: Pittsburgh Pisces
Triple: [The Fish That Saved Pittsburgh, fictionalTeamName, Pittsburgh Pisces]

Generated description

Pittsburgh Pisces is the fictional professional basketball team featured in the 1979 sports comedy film "The Fish That Saved Pittsburgh."

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_69f76de6d39c8190bb11342e4b91ff2b`	completed	May 3, 2026, 3:46 p.m.
NER	Named-entity recognition	`batch_69ff05bb0a908190a3293114f564f398`	completed	May 9, 2026, 10 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a380fc4de508190ab8028fd8754e85b`	completed	June 21, 2026, 4:22 p.m.
NEDg	Description generation	`batch_6a38112adef081909238815060b6af80`	completed	June 21, 2026, 4:28 p.m.
NED2	Entity disambiguation (via description)	`batch_6a3811d3a5c08190b3524a968483243e`	completed	June 21, 2026, 4:31 p.m.

Created at: May 3, 2026, 4:03 p.m.