Triple

T33083619
Position Surface form Disambiguated ID Type / Status
Subject Helvis of Ramla E846571 entity
Predicate child P120 FINISHED
Object Baldwin of Ibelin
Baldwin of Ibelin was a prominent 12th-century nobleman and lord in the Crusader Kingdom of Jerusalem, influential in the politics and military affairs of the Latin East.
E2056506 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: Baldwin of Ibelin | Statement: [Helvis of Ramla, child, Baldwin of Ibelin]
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: Baldwin of Ibelin
Triple: [Helvis of Ramla, child, Baldwin of Ibelin]
Generated description
Baldwin of Ibelin was a prominent 12th-century nobleman and lord in the Crusader Kingdom of Jerusalem, influential in the politics and military affairs of the Latin East.

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_69f34954d46c8190a04a159cc5f99efd completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d61f114081908d17a5b53ecc14b7 completed May 3, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35a654998c81909509e1ab5cf0a70d completed June 19, 2026, 8:28 p.m.
NEDg Description generation batch_6a35a8f71f108190b3deafe9caa2772d completed June 19, 2026, 8:39 p.m.
NED2 Entity disambiguation (via description) batch_6a35a96a0d3081908e67533333bcd739 completed June 19, 2026, 8:41 p.m.
Created at: May 1, 2026, 1:26 a.m.