Triple

T26985308
Position Surface form Disambiguated ID Type / Status
Subject Ibrahim Agha E679720 entity
Predicate conflict P12 FINISHED
Object Battle of Sidi Ferruch
The Battle of Sidi Ferruch was an 1830 engagement during the French invasion of Algiers, marking a decisive French victory that paved the way for the colonization of Algeria.
E1753419 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: Battle of Sidi Ferruch | Statement: [Ibrahim Agha, conflict, Battle of Sidi Ferruch]
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: Battle of Sidi Ferruch
Triple: [Ibrahim Agha, conflict, Battle of Sidi Ferruch]
Generated description
The Battle of Sidi Ferruch was an 1830 engagement during the French invasion of Algiers, marking a decisive French victory that paved the way for the colonization of Algeria.

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_69eeeb5138ac8190b3c273ddc659a54f completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f6215954f8819092cf882ca976fafa completed May 2, 2026, 4:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123aae3bcc8190b0e51c2950dc60cc completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123b7235d081909cc231c0b1cc9b30 completed May 23, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_6a123c1995688190a630954191d4e905 completed May 23, 2026, 11:45 p.m.
Created at: April 27, 2026, 6:48 a.m.