Triple

T25751852
Position Surface form Disambiguated ID Type / Status
Subject Avraham Gombiner E648486 entity
Predicate alsoKnownAs P39 FINISHED
Object Avraham Abele Gombiner
Avraham Abele Gombiner was a 17th-century Polish rabbi and Talmudic scholar best known for his halachic commentary "Magen Avraham" on the Shulchan Aruch, Orach Chaim.
E1698489 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: Avraham Abele Gombiner | Statement: [Avraham Gombiner, alsoKnownAs, Avraham Abele Gombiner]
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: Avraham Abele Gombiner
Triple: [Avraham Gombiner, alsoKnownAs, Avraham Abele Gombiner]
Generated description
Avraham Abele Gombiner was a 17th-century Polish rabbi and Talmudic scholar best known for his halachic commentary "Magen Avraham" on the Shulchan Aruch, Orach Chaim.

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_69e7ab314d788190b3abe19e114080e1 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fd7ef3c48190b5f1b3b4e9cecb2b completed May 2, 2026, 1:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da05d42081908fc81117467a86e3 completed May 22, 2026, 10:34 p.m.
NEDg Description generation batch_6a10dc8845748190ba1fffaed79db4a5 completed May 22, 2026, 10:45 p.m.
NED2 Entity disambiguation (via description) batch_6a10dcebc9d88190b8b2149afa3c31ee completed May 22, 2026, 10:47 p.m.
Created at: April 22, 2026, 4:36 a.m.