Triple

T29545781
Position Surface form Disambiguated ID Type / Status
Subject Battle of Tabsor E749626 entity
Predicate location P40 FINISHED
Object Tabsor salient
Tabsor salient was a strategically important protrusion in the Ottoman defensive line in Palestine during World War I, heavily contested during the British-led offensives in 1918.
E1872707 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: Tabsor salient | Statement: [Battle of Tabsor, location, Tabsor salient]
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: Tabsor salient
Triple: [Battle of Tabsor, location, Tabsor salient]
Generated description
Tabsor salient was a strategically important protrusion in the Ottoman defensive line in Palestine during World War I, heavily contested during the British-led offensives in 1918.

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_69f0bd48691081908cecad39bac591e0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66cf25fa88190a158d58d32872c01 completed May 2, 2026, 9:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260c4184648190b21de658660fe246 completed June 8, 2026, 12:26 a.m.
NEDg Description generation batch_6a261065aefc8190b2945fba730d44ba completed June 8, 2026, 12:44 a.m.
NED2 Entity disambiguation (via description) batch_6a2614a384988190939b488b13114459 completed June 8, 2026, 1:02 a.m.
Created at: April 28, 2026, 5:07 p.m.