Triple

T30471663
Position Surface form Disambiguated ID Type / Status
Subject The Fabled City E775318 entity
Predicate hasPart P35 FINISHED
Object The Lights Are On in Spidertown
"The Lights Are On in Spidertown" is a story set in the shared universe of The Fabled City, likely exploring one of its distinctive locales or episodes within that larger fantastical setting.
E1916975 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: The Lights Are On in Spidertown | Statement: [The Fabled City, hasPart, The Lights Are On in Spidertown]
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: The Lights Are On in Spidertown
Triple: [The Fabled City, hasPart, The Lights Are On in Spidertown]
Generated description
"The Lights Are On in Spidertown" is a story set in the shared universe of The Fabled City, likely exploring one of its distinctive locales or episodes within that larger fantastical setting.

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_69f22497341481909c21ba329fadaa6b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68715ad9c8190a5f41313c3f11190 completed May 2, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27ac1eedac8190bcd6a078cd2f0684 completed June 9, 2026, 6:01 a.m.
NEDg Description generation batch_6a27acd96c448190b597825a60709338 completed June 9, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a27ad7fb6408190a3a03a28aaa3dcc0 completed June 9, 2026, 6:06 a.m.
Created at: April 29, 2026, 8:11 p.m.