Triple

T36339910
Position Surface form Disambiguated ID Type / Status
Subject 張學良 E894884 entity
Predicate birthPlace P1 FINISHED
Object 遼寧省海城縣牛莊
遼寧省海城縣牛莊是中國東北地區的一個城鎮，因為是近代著名軍政領袖張學良的出生地而聞名。
 E2180404 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: 遼寧省海城縣牛莊 | Statement: [張學良, birthPlace, 遼寧省海城縣牛莊]
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: 遼寧省海城縣牛莊
Triple: [張學良, birthPlace, 遼寧省海城縣牛莊]
Generated description
遼寧省海城縣牛莊是中國東北地區的一個城鎮，因為是近代著名軍政領袖張學良的出生地而聞名。

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_69f76e4e90148190b02fe52593c70b5b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7ba9cd6408190ba500b3e3e697275 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a31e69448190a4771e22bdd11906 completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a3e4a9488190a77ea18c86b5af48 completed June 22, 2026, 9:06 p.m.
NED2 Entity disambiguation (via description) batch_6a39a49278088190b10c591fec7c42e2 completed June 22, 2026, 9:09 p.m.
Created at: May 3, 2026, 4:09 p.m.