Triple

T27113996
Position Surface form Disambiguated ID Type / Status
Subject The First Half of My Life E686790 entity
Predicate alsoKnownAs P39 FINISHED
Object Wo De Qian Ban Sheng
Wo De Qian Ban Sheng is a popular Chinese television drama series that follows a woman’s emotional and professional rebirth after divorce and personal crisis.
E1757766 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: Wo De Qian Ban Sheng | Statement: [The First Half of My Life, alsoKnownAs, Wo De Qian Ban Sheng]
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: Wo De Qian Ban Sheng
Triple: [The First Half of My Life, alsoKnownAs, Wo De Qian Ban Sheng]
Generated description
Wo De Qian Ban Sheng is a popular Chinese television drama series that follows a woman’s emotional and professional rebirth after divorce and personal crisis.

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_69ef148accd48190b6ed6e13a15f2a4f completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f6240450088190af486dbde3daeacb completed May 2, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a124811f11881909ed52a475884b0b8 completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a1249280a048190bb0003079b8dfab4 completed May 24, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a1249ec94e48190acbcd83ba6d923ea completed May 24, 2026, 12:44 a.m.
Created at: April 27, 2026, 8:55 a.m.