Triple

T37441765
Position Surface form Disambiguated ID Type / Status
Subject Xavier Sala-i-Martin E930437 entity
Predicate notableWork P4 FINISHED
Object I Just Ran Two Million Regressions
"I Just Ran Two Million Regressions" is a widely cited economics paper by Xavier Sala-i-Martin that uses extensive regression analysis to investigate the robustness of empirical determinants of economic growth.
E2227801 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: I Just Ran Two Million Regressions | Statement: [Xavier Sala-i-Martin, notableWork, I Just Ran Two Million Regressions]
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: I Just Ran Two Million Regressions
Triple: [Xavier Sala-i-Martin, notableWork, I Just Ran Two Million Regressions]
Generated description
"I Just Ran Two Million Regressions" is a widely cited economics paper by Xavier Sala-i-Martin that uses extensive regression analysis to investigate the robustness of empirical determinants of economic growth.

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_69f76ec0b9488190b7a4fae632bd1d2f completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8ddc1388819091fc7ef278d832ee completed May 6, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40825b4cc8819086490ef03d79b13a completed June 28, 2026, 2:09 a.m.
NEDg Description generation batch_6a408626402c81909022ea8a43da5178 completed June 28, 2026, 2:25 a.m.
NED2 Entity disambiguation (via description) batch_6a40869086208190a3bc5409cc268462 completed June 28, 2026, 2:27 a.m.
Created at: May 3, 2026, 4:17 p.m.